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August 21, 2024

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Sharing risk to avoid power outages in an era of extreme weather

by Rob Jordan, Stanford University

This summer's Western heat waves raise the specter of recent years' rotating power outages and record-breaking electricity demand in the region. If utilities across the area expanded current schemes to share electricity, they could cut outage risks by as much as 40%, according to new research by the Climate and Energy Policy Program at the Stanford Woods Institute for the Environment.

The study highlights how such a change could also help ensure public opinion and policy remain favorable for renewable energy growth. It comes amid debate over initiatives like the West-Wide Governance Pathways Initiative , an effort led by Western regulators to create a multi-state grid operations and planning organization.

"Extreme weather events disregard state and electric utilities' boundaries, and so will the solution needed to mitigate the impact," said study co-author Mareldi Ahumada-Paras, a postdoctoral scholar in energy science and engineering in the Stanford Doerr School of Sustainability. "Greater regional cooperation can benefit reliability under wide-spread stress conditions."

The new abnormal

Across the West, electricity providers are struggling with three new realities. Demand and resource availability are becoming harder to predict because of factors ranging from more frequent and widespread weather extremes to the proliferation of rooftop solar installations to more frequent and widespread weather extremes.

Rapid growth of renewable energy, such as wind and solar, along with energy storage options requires new operating and planning strategies for meeting demand. On top of these trends, a patchwork of state and federal clean energy goals creates different incentives that influence utilities' operation and planning differently.

"New grid management approaches can capitalize on the opportunities created by our rapidly changing electricity system and address increasing stress from extreme heat, drought, and other climate-related events," said study co-author Michael Mastrandrea, research director of the Climate and Energy Policy Program.

The study focuses on the power grid that stretches from the West Coast to the Great Plains and from western Canada to Baja California. In recent years, extreme heat events and severe droughts have put major demand stresses on the grid and reduced hydropower availability.

The researchers used power system optimization models to simulate grid operations under stress conditions based on those experienced during a 2022 California heat wave that saw record-breaking energy demand.

Their simulations demonstrated that expanding the area of cooperation could reduce the risk of power outages by as much as 40%, reduce the amount of unserved energy—when electricity demand exceeds supply—by more than half, and increase reliability.

Policy and public opinion

The researchers refer to these estimates as "illustrative and directional" because incomplete information makes it hard to precisely simulate how those responsible for ensuring power system reliability within specific service territories will respond to stress conditions.

Still, the results highlight how expanded cooperation among utilities can improve responses to local shortages and excesses, offer greater flexibility in managing unexpected disruptions and balancing supply and demand, and ensure reliable electricity supply during extreme weather events .

Expanded cooperation among utilities could also maximize the value of the region's growing renewable energy portfolio, according to the researchers. Renewable power generation, such as wind and solar, can be variable since the wind doesn't always blow and the sun only shines so many hours per day.

Expanding cooperation across a larger geographic area can ensure that renewable power generation is used (or stored for later) when it is available. Critics of these sources are also likely to blame them for major power outages , according to the researchers, feeding a narrative that could sour public opinion and lead to policies slowing the adoption or expansion of clean energy.

"Our work shows how greater cooperation isn't just about dollars and cents for utilities and their customers," said study co-author Michael Wara, director of the Climate and Energy Policy Program at the Stanford Woods Institute for the Environment.

"It's about keeping the lights on as we confront the challenge of the energy transition and the growing impacts of climate change."

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Guest Essay

The Electric Grid Is a Wildfire Hazard. It Doesn’t Have to Be.

By Michael E. Webber

Dr. Webber is a professor of public affairs and engineering at the University of Texas and the chief technology officer of Energy Impact Partners, a venture fund that has investments in technologies to improve the electrical grid.

One year after the deadly wildfires on Maui and a few weeks after Hurricane Beryl knocked out power to millions of Houston-area residents, it has become abundantly clear that our electricity grid is dangerously vulnerable.

The accumulating wear and tear on the components that hold the grid together, combined with weather that has often been hotter and stormier in some regions, means the wildfires and sustained blackouts may be a preview of how an aging grid could falter spectacularly as weather becomes more extreme and demand for electricity continues to rise.

The National Academy of Engineering calls the power grid the most important innovation of the 20th century, and with the greater electrification of society it will become even more critical. The sprawling system of transmission lines, power plants and transformers connects communities across the United States. Many of the components that tie the system together — utility poles, transmission towers and power lines — haven’t been modernized or upgraded since they were built, often decades ago. The consequences of this neglect, as we have seen, can be catastrophic.

This past spring, a decayed utility pole broke in high winds in the Texas Panhandle, causing power wires to fall on dry grass and igniting the largest fire in the state’s history. Two people died and more than one million acres burned. The Maui wildfire that killed more than 100 people and destroyed the historic town of Lahaina last year began after winds knocked down power lines, also igniting dry grass. The 2018 Paradise fire in California started when a live wire broke free of a tower that was a quarter-century past what the utility Pacific Gas & Electric considered its “useful life.” Eighty-five people died and nearly 14,000 homes were destroyed.

Maintenance budgets for the grid have been insufficient for decades. Solutions exist to reduce the risk of wildfires, such as burying power lines, inspecting every mile of the system, installing modern sensors for early detection of wildfire risk, and controls that allow for the remote disconnection of vulnerable sections of the grid. Granted, these fixes are expensive. To bury transmission lines can easily cost $3 million to $5 million a mile. But research from Lawrence Berkeley National Lab concluded that these overhauls also save money in lives protected and damage avoided in storm-prone areas.

So why haven’t made these investments been made?

State regulators overseeing electric utilities pressure them to keep rates low, which means smaller budgets for trimming trees, modernizing lines or deploying autonomous inspection technologies. Regulators in California recently scaled back Pacific Gas & Electric’s plan to bury 10,000 miles of transmission lines in fire- prone areas. In Texas, regulators have few wildfire regulations for the power sector.

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• Environment /

Summer blackouts are increasing in the US

Weather-related power outages have become a much bigger problem in the summertime than they used to be, a new analysis shows..

By Justine Calma , a senior science reporter covering energy and the environment with more than a decade of experience. She is also the host of Hell or High Water: When Disaster Hits Home , a podcast from Vox Media and Audible Originals.

Share this story

The US has dealt with 60 percent more weather-related outages during warmer months over the past decade than it did during the 2000s, according to data crunched by the nonprofit research organization Climate Central .

It’s a trend that raises health risks as the planet heats up. Climate change supercharges disasters like storms and wildfires that often cut off power. Soaring demand for air conditioning also stresses out the grid. All of this can leave people without life-saving cooling or electric medical devices at times when they’re most vulnerable.

Climate Central collected data from the Department of Energy on outages that took place between 2000 and 2023. It looked specifically at periods between May and September each year, warmer months when people rely on air conditioning the most. The analysis focused on blackouts attributed to bad weather or wildfires, which hot and dry conditions can exacerbate.

The findings fall in line with other surveys of power outages over time in the US. Americans experienced an average of 5.5 hours of electricity interruptions in 2022 compared to roughly 3.5 hours in 2013, according to the US Energy Information Administration (EIA). That includes all kinds of power disruptions throughout the year. But the culprit behind longer outages is “major events,” including weather disasters. Without those big events, the length of outages would have mostly flatlined over the past decade.

Certain areas have fared worse than others over the years, the Climate Central analysis shows. The South experienced more weather-related blackouts than any other region during warmer months, with 175 outages between 2000 and 2023. Texas leads the nation as the state with the most weather-related outages, with 107 over the same period.

The Lone Star State is in a unique position because most of the state doesn’t connect to larger power grids that span across eastern and western states . That makes it harder for Texas to make up for energy shortfalls by relying on its neighbors. But the Texas power grid has also been hit hard by extreme weather. Just this summer, Hurricane Beryl led to widespread blackouts and at least 11 heat-related deaths reported in the aftermath of the storm.

The nation’s aging grid infrastructure could certainly use an upgrade to make it more resilient to a changing climate . Burying power lines can safeguard them from extreme weather in some scenarios. Residential solar energy systems and microgrids can help keep the lights on for homes even if power plants or power lines go down in a disaster. And switching from fossil fuels to renewable energy would prevent those climate-related disasters from growing into bigger monsters in the first place.

• The world’s power grids, 50 million miles’ worth, need a major overhaul
• When will Puerto Rico have power?

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• Extreme weather is leading to more frequent power grid strain and electricity outages.
• There are a range of regional cooperation agreements among utilities to share electricity.
• Expanding cooperation areas in the West could cut outage risks by as much as 40%.
• Expanding cooperation among electricity providers could also help ensure public opinion and policy remain favorable for renewable energy growth.

This summer’s Western heat waves raise the specter of recent years’ rotating power outages and record-breaking electricity demand in the region. If utilities across the area expanded current schemes to share electricity, they could cut outage risks by as much as 40%, according to new research by the  Climate and Energy Policy Program  at the  Stanford Woods Institute for the Environment . The study highlights how such a change could also help ensure public opinion and policy remain favorable for renewable energy growth. It comes amid debate over initiatives like the  West-Wide Governance Pathways Initiative , an effort led by Western regulators to create a multi-state grid operations and planning organization.

“Extreme weather events disregard state and electric utilities’ boundaries, and so will the solution needed to mitigate the impact,” said study co-author  Mareldi Ahumada-Paras , a postdoctoral scholar in energy science and engineering in the  Stanford Doerr School of Sustainability .   “Greater regional cooperation can benefit reliability under wide-spread stress conditions.”

The new abnormal 

Across the West, electricity providers are struggling with three new realities. Demand and resource availability are becoming harder to predict because of factors ranging from more frequent and widespread weather extremes to the proliferation of rooftop solar installations to more frequent and widespread weather extremes. Rapid growth of renewable energy, such as wind and solar, along with energy storage options requires new operating and planning strategies for meeting demand. On top of these trends, a patchwork of state and federal clean energy goals creates different incentives that influence utilities’ operation and planning differently. 

“New grid management approaches can capitalize on the opportunities created by our rapidly changing electricity system and address increasing stress from extreme heat, drought, and other climate-related events,” said study co-author  Michael Mastrandrea , research director of the Climate and Energy Policy Program. 

The study focuses on the power grid that stretches from the West Coast to the Great Plains and from western Canada to Baja California. In recent years, extreme heat events and severe droughts have put major demand stresses on the grid and reduced hydropower availability.

The researchers used power system optimization models to simulate grid operations under stress conditions based on those experienced during a 2022 California heat wave that saw record-breaking energy demand. Their simulations demonstrated that expanding the area of cooperation could reduce the risk of power outages by as much as 40%, reduce the amount of unserved energy – when electricity demand exceeds supply – by more than half, and increase reliability.

Grid Regionalization in the West webinar

A related webinar on Aug. 22 will present the study’s results and feature energy experts in a discussion about efforts to expand cooperation in Western electricity markets.

Policy and public opinion 

The researchers refer to these estimates as “illustrative and directional” because incomplete information makes it hard to precisely simulate how those responsible for ensuring power system reliability within specific service territories will respond to stress conditions. Still, the results highlight how expanded cooperation among utilities can improve responses to local shortages and excesses, offer greater flexibility in managing unexpected disruptions and balancing supply and demand, and ensure reliable electricity supply during extreme weather events.

Expanded cooperation among utilities could also maximize the value of the region’s growing renewable energy portfolio, according to the researchers. Renewable power generation, such as wind and solar, can be variable since the wind doesn’t always blow and the sun only shines so many hours per day. Expanding cooperation across a larger geographic area can ensure that renewable power generation is used (or stored for later) when it is available. Critics of these sources are also likely to blame them for major power outages, according to the researchers, feeding a narrative that could sour public opinion and lead to policies slowing the adoption or expansion of clean energy.  

“Our work shows how greater cooperation isn’t just about dollars and cents for utilities and their customers,” said study co-author  Michael  Wara , director of the  Climate and Energy Policy Program  at the  Stanford Woods Institute for the Environment . “It’s about keeping the lights on as we confront the challenge of the energy transition and the growing impacts of climate change.”

For more information

Wara and Mastrandrea are also senior director for policy and director for policy, respectively, in the Stanford Doerr School of Sustainability’s  Sustainability Accelerator .

Media contacts

Michael Wara, Stanford Woods Institute for the Environment: [email protected] Michael Mastrandrea, Stanford Woods Institute for the Environment: [email protected] Mareldi Ahumada-Paras, Stanford Doerr School of Sustainability:  [email protected] Rob Jordan, Stanford Woods Institute for the Environment: (650) 721-1881, [email protected]

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Power outages and community health: a narrative review

Joan a. casey.

1 Columbia University Mailman School of Public Health, Department of Environmental Health Sciences, New York, NY, USA

Mihoka Fukurai

2 Columbia University Mailman School of Public Health, Department of Epidemiology, New York, NY, USA, USA

Diana Hernández

3 Columbia University Mailman School of Public Health, Department of Sociomedical Sciences, New York, NY, USA

Satchit Balsari

4 Department of Emergency Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA

5 FXB Center for Health and Human Rights, Harvard TH Chan School of Public Health, Boston, MA, USA

Mathew V. Kiang

6 Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA

Associated Data

Purpose of review:.

Power outages, a common and underappreciated consequence of natural disasters, are increasing in number and severity due to climate change and aging electricity grids. This narrative review synthesizes the literature on power outages and health in communities.

Recent findings:

We searched Google Scholar and PubMed for English-language studies with titles or abstracts containing “power outage” or “blackout.” We limited papers to those that explicitly mentioned power outages or blackouts as the exposure of interest for health outcomes among individuals living in the community. We also used the reference list of these studies to identify additional studies. The final sample included 50 articles published between 2004–2020, with 17 (34%) appearing between 2016–2020. Exposure assessment remains basic and inconsistent, with 43 (86%) of studies evaluating single, large-scale power outages. Few studies used spatial and temporal control groups to assess changes in health outcomes attributable to power outages. Recent research linked data from electricity providers on power outages in space and time and included factors such as number of customers affected and duration to estimate exposure.

The existing literature suggests that power outages have important health consequences ranging from carbon monoxide poisoning, temperature-related illness, gastrointestinal illness, and mortality to all-cause, cardiovascular, respiratory, and renal disease hospitalizations, especially for individuals relying on electricity-dependent medical equipment. Nonetheless the studies are limited and more work is needed to better define and capture the relevant exposures and outcomes. Studies should consider modifying factors such as socioeconomic and other vulnerabilities as well as how community resiliency can minimize the adverse impacts of widespread major power outages.

INTRODUCTION

In August 2003, over 50 million Americans and Canadians lost power for up to four days due to a surge of electricity along faulty transmission lines ( 1 ). In China, ice-coated transmission lines and towers collapsed during a severe winter storm in 2008, interrupting electric service to 200 million people ( 2 ). Meanwhile, hot weather and related air conditioner use triggered a blackout affecting 8 million people in Baku, Azerbaijan in July 2018 ( 1 ). The largest blackout in history affected at least 600 million people across India in July 2012 ( 3 ). The frequency and severity of these events will increase with population growth and climate change, as infrastructure damage from intense storms and floods, hydropower shortage from droughts, and increased demand as temperatures rise and strain an aging electricity grid ( 4 - 6 ).

Power outages worldwide

Today, South Asia has the highest system average interruption frequency index (SAIFI). The average business there experienced 26 outages per month in 2019 ( 7 ). However, even businesses in Organisation for Economic Co-operation and Development (OECD) countries experienced one power outage every other month in 2019. Outages last longest, on average, in Latin America and the Caribbean (8 hours) and Sub-Saharan Africa (7.5 hours), compared to just 2.5 hours in East Asia ( 8 ). The United States (U.S.) Energy Information Administration predicts that global electricity production will increase by 75%, from 20 trillion kilowatt-hours (kWh) in 2018 to 45 trillion kWh in 2050, driven in large part by demand in non-OECD countries ( 9 ). This increased demand will result in more power outages, with unique economic, social, and health consequences, of which we review that latter.

Causes and costs of U.S. power outages

In the U.S., major power outages increased 10-fold between 1984–2012 with the average household experiencing 470 minutes without power in 2017 ( 11 , 12 ). Large blackouts, disturbances that interrupt more than 300MW (enough power for ~50,000 homes) or 50,000 customers and require reporting to the U.S. Department of Energy ( 13 ), occur more commonly in the winter and summer and year-round during the mid-afternoon ( 14 ). Electromagnetic events and intentional cyber-physical attacks caused >25% of total U.S. power outages between 2000-2016 ( Figure 1A ) ( 10 , 15 ). Such attacks present substantial risk to the electricity grid and could result in an outage that stretches for months across wide geographies, especially if timed after a natural disaster ( 16 ). Most widespread power outages were caused by severe weather ( Figure 1B ) and Florida, California, New York, and Michigan were hit hardest with 25.3 million, 22.2 million, 18.3 million, and 12.4 million affected customers, respectively ( 15 ).

A) Number of large power outages by cause between 2000-2016. B) Count of outages by primary cause type by state between 2000-2016. For example, Texas had 65 power outages caused by severe weather between 2000-2016. Data from Mukherjee et al. 2018 ( 10 ), which they assembled from publicly-available datasets. A large power outage is defined by the U.S. Department of Energy as: 50,000+ customers affected or an unplanned loss of 300 MW.

Outages, particularly those related to weather, are almost always accompanied by intersecting and related phenomena that result in economic, social, and health damages ( Figure 2 ). Economically, they interrupt business, cripple the internet, and halt many forms of transportation ( 8 ). The 2003 Northeast Blackout in Canada and the U.S. cost between $4-10 billion ( 17 ), and electricity infrastructure repairs alone cost $3.5 billion after Hurricane Sandy ( 18 ). Social costs include increased crime, motor vehicle crashes, psychosocial stress, and interrupted communication between emergency services, delivery of clean water, and waste removal ( 3 , 12 , 19 , 20 ). Although, altruistic acts, including providing assistance to others, donating money, assisting with traffic, may also increase ( 19 - 22 ). Several factors influence the severity of economic, social, and health costs of power outages including outage frequency, duration, timing, and geographic range, as well as mitigation measures, population preparedness, and prior experience ( 19 , 23 ).

We illustrate co-occurring factors such as displacement, extreme temperatures, and air pollution, as well as vulnerability factors that might increase the risk of adverse health outcomes during power outages, including baseline health status, socioeconomic status, and social support.

Medically high-risk groups during power outages

Certain subgroups have higher risk of adverse health outcomes during power outages. These include older adults, those reliant on electricity-dependent durable medical equipment (DME, e.g., oxygen concentrators), those unable to evacuate, including nursing home patients, those reliant on others to complete activities of daily living, the heat/cold susceptible, and those with underlying conditions exacerbated by the inciting events, such as respiratory, cardiovascular, and renal disease ( 23 - 25 ). The number of electricity-dependent individuals is anticipated to grow in the coming years ( 23 , 25 ); numbers already trend upward and rate of DME use appears higher among lower socioeconomic status individuals ( 26 ).

Documented disparities in power outage preparedness and exposure

Evidence from the U.S. suggests older adults, poorer families, and individuals of non-Hispanic Black and Hispanic race/ethnicity are least likely to have a three-day supply of food, drinking water, and medication, a preparedness measure for power outages ( 27 - 29 ). In New York City, only 58% of 887 people surveyed were prepared for a disaster; preparedness dipped to 45% among households with income <$30,000 and to 28% among primary Spanish-speakers ( 29 ). Generator cost ($2-5,000) may price out lower socioeconomic status families and those living in public housing or apartment buildings that prohibit generators ( 21 , 29 ). Finally, power outages may last longer in lower socioeconomic status or communities of color ( 30 - 34 ), where impacts may already be greater. For example, in Florida after Hurricane Irma, higher income individuals evacuated farther and to destinations with lower power outage rates compared to their lower income counterparts ( 33 ). After Hurricane Maria, satellite imagery of Puerto Rico suggested that households with power restored in Stage 1 earned almost double the income of households with power restored in Stages 2-3 ( 32 ). After Hurricane Sandy in New Jersey, non-Hispanic White individuals had the longest duration outages (11.2 days compared to 8.2 days for African Americans) ( 34 ). Such disparities put these already-vulnerable groups at increased risk of adverse power outage-related health outcomes.

Goal of this review

This review focuses on blackouts—the unavailability of electric power in an area—and does not address issues of energy poverty, a separate and important predictor of health ( 35 , 36 ). In addition, we do not cover challenges faced by healthcare facilities during power outages. In this narrative review, we highlight themes in the current scholarship on power outages and community health and identify future avenues for research.

We conducted searches via Google Scholar and PubMed in spring 2020 for studies written in English with titles or abstracts containing “power outage” or “blackout.” We limited papers to those that explicitly mentioned power outages or blackouts as the exposure of interest for health outcomes among individuals living in the community. The reference lists of the identified studies were also examined to identify additional relevant articles. We screened the articles to include only original primary research published between January 2004 and June 2020 that explicitly mentioned power outage or blackout as an exposure of interest. The final sample included 50 articles spanning power outage events from 1977 to 2019 ( Figure 3 ). The majority (72%) of the studies evaluated health outcomes in the US, but we collected literature from across the globe ( Appendix Figure 1 ). Non-US articles tended to focus on interrupted healthcare ( 37 , 38 ), which was outside the scope of this review.

Dashed outlines represent outages caused by technological failure and solid outlines those caused by severe weather. Numbers in square brackets denote the number of studies evaluating the specific outage and fill colors get closer to red with more studies evaluating the outage.

Exposure assessment

Single, large-scale power outages..

Nearly all studies evaluated single, large-scale power outages. While the definition of large-scale varied from study to study, many met the U.S. Department of Energy criteria: 50,000+ customers affected or an unplanned loss of 300 MW ( 13 ). Researchers assumed individuals experienced the outage if they lived or attended a healthcare facility in the region where the outage occurred. Most studies relied on pre-post outage temporal comparisons to draw inference ( 20 , 28 , 39 - 53 ) or only described health outcomes after the outage ( 54 - 71 ) ( Figure 4 A). Eight studies of single outages also incorporated geographic variability in outage distribution in the study design, in addition to using pre-post outage health measures ( 72 - 79 ).

Most studies evaluated a single outage by describing outcomes after the event among the exposed population (single outage, no temporal comparison). Eight studies evaluated a single outage but used both spatial and temporal comparison groups to make inference (single outage, temporal + spatial comparison). Three studies used measures of long-term exposure from multiple outages to assign levels of power outage exposure to the study population (multiple outages, measure of long-term exposure).

Multiple power outages.

Seven studies evaluated multiple power outages ( 30 , 80 - 85 ), with three using outage frequency to characterize long-term exposure ( 82 , 84 , 85 ). Others conducted longitudinal analyses. In South Africa, Gehringer and colleagues used a combination of government data, Facebook, and the local electric utility’s Twitter handle to track daily load shedding events (halted electricity distribution due to demand exceeding supply), including outage duration ( 30 ). Koroglu used standard electricity reliability data from the Maharashtra State Electricity Distribution Company in India to characterize monthly SAIFI and system average interruption duration indices (SAIDI) values statewide ( 83 ). Zhang and colleagues linked power outage records, including total number of customers affected, from the New York State Department of Public Service (NYSPS) between 2001-2013 to the power-operating division-level (~1,700 divisions exist in New York with an average population of ~11,000 people each). They created daily exposure metrics based on proportion of customers affected and duration (in days) of power outages. Likewise, Dominianni et al. used half-hourly NYSPS data to identify outages within each of New York City’s (NYC) 66 electricity grid networks ( 80 ). They defined the entire grid network area as exposed on a given day if >1,000 people were without power during the warm-season and if >75 people were without power during the cold-season. Different cutpoints were used because fewer people experienced outages during the cold season.

Carbon monoxide poisoning.

Twenty-three (48%) of studies included evaluated carbon monoxide (CO) poisoning ( 44 , 45 , 50 , 51 , 54 , 55 , 57 - 62 , 64 - 66 , 69 - 72 , 76 , 77 , 85 , 86 ), a topic previously reviewed ( 87 - 89 ). CO is a colorless, odorless, and tasteless gas, formed by incomplete combustion of carbon compounds. Because hemoglobin binds 250x more readily with CO than with oxygen, prolonged exposure leads to cellular hypoxia, ischemia, and death ( 90 ).

In the 23 reviewed articles, indoor use of charcoal and gasoline-powered generators caused the majority of CO poisonings. The most common symptoms of CO poisoning were headache, nausea, vomiting, dizziness, loss of consciousness, and death. The majority of studies identified CO poisoning using medical chart reviews including emergency department (ED) visits ( 50 , 54 , 55 , 57 , 60 , 64 - 66 , 69 - 72 , 77 ), hospitalizations ( 58 , 69 - 71 , 76 ), and emergency medical service (EMS) and poison control calls ( 28 , 44 , 45 , 58 , 59 , 65 , 69 , 72 ) coded as CO poisoning-related; several studies used laboratory confirmation or reported serum carboxyhemoglobin (COHb) levels ( 44 , 54 , 55 , 59 - 61 , 64 , 70 , 91 ). Many studies reported fatalities, particularly in the several days following storms ( 54 , 55 , 57 , 59 - 62 , 65 , 69 - 71 , 85 ). Over 50% of CO poisoning studies reported the use of hyperbaric oxygen therapy ( 44 , 54 , 55 , 58 , 59 , 61 , 64 , 65 , 69 - 72 , 91 ), and higher COHb levels may be related to persistent cognitive and psychiatric changes after CO poisoning ( 91 ). In many cases, children ( 54 , 55 , 59 , 72 ), older adults ( 61 , 62 , 65 ), immigrants ( 60 , 65 ), and people of color ( 55 , 60 , 64 , 65 , 70 ) were disproportionately affected. Qualitative methods can provide key insights not otherwise captured. For example, Styles and colleagues also found that 62% of non-Hispanic White generator/charcoal grill/heater operators reported hearing warnings about CO poisoning in the year prior compared to just 30% of those in other racial/ethnic groups ( 70 ) and Van Sickle et al. determined fear of theft was the most common reason to place a generator indoors ( 71 ).

While most studies only catalogued CO poisoning events following power outages, a few employed a comparison time period ( 28 , 45 , 50 , 72 , 76 , 77 ), allowing authors to determine if more CO poisoning occurred than expected following power outages. After the Great East Japan Earthquake of 2011, Nakajima and colleagues found 13.5x the odds of CO poisoning among patients in the disaster area (including power outage exposure) from March 11 to April 9, 2011 compared to the same dates in 2012 ( 76 ). A spatial control also revealed higher counts of CO poisoning in the disaster area versus an unexposed region. Johnson-Arbor compared two major storms in Connecticut in 2011 and 2013, where the 2011 storm resulted in 11x the number of individuals losing power and 5x the number of CO poisonings ( 44 ).

All-cause, cardiovascular, respiratory, and renal disease healthcare visits.

In general, hospitals see fewer patients in the days leading up to storms ( 42 ), whereas more patients arrive during and after outages, often with respiratory, cardiovascular, or renal disease exacerbations ( 30 , 40 , 42 , 46 , 47 , 53 , 68 , 80 , 81 ). In a comprehensive study, Dominianni et al. evaluated three major NYC outages (1999, 2003, 2006) and localized warm- and cold-weather outages within NYC ( 80 ). In models accounting for temperature, day of week, and seasonal and long-term trends, they confirmed prior findings of increased cardiovascular and respiratory disease hospitalizations during the 2003 outage and found new evidence of elevated risk of renal disease hospitalizations during warm-season power outages and cardiovascular disease hospitalizations during cold-season power outages. Zhang and colleagues also illustrated the utility of using daily sub-city level power outage data in their study of chronic obstructive pulmonary disease (COPD) hospitalizations statewide. They used power-operating division-level (~11,000 residents per division) between 2001-2013 in New York and found the largest increases in COPD hospitalizations during the first three days after power outages, where 23% of COPD hospitalizations on power outages days could be attributed to the outage itself ( 81 ). Compared to non-power outage periods, COPD patients arriving for care during power outages had a higher number of comorbidities and healthcare costs. Interrupted use of nebulizers, and oxygen and bilevel positive airway pressure machines, as well as sensitivity of COPD patients to changing indoor conditions (e.g., lack of air conditioning or dehumidifiers) likely explained the large increase in hospitalizations.

Many acute care visits related to cardiovascular and respiratory disease exacerbation during blackouts appear to result from failure of electricity-dependent medical devices ( 41 , 42 , 46 , 50 , 51 , 63 , 67 , 68 , 80 , 81 , 92 ). For example, after the 2011 Great East Japan Earthquake, 75% of 24 new pediatric inpatients at Tohoku University Hospital relied on DME, including 13 children using ventilators ( 76 ). After Hurricane Sandy, ED visits at Beth Israel Medical Center related to respiratory device failure and “power outage” increased in all age groups and peaked the day following the disaster ( 41 ).

Older adults and children may be at particular risk during power outages. Unlike many other NYC hospitals in downtown Manhattan, Beth Israel Medical Center remained open after Hurricane Sandy and their electronic health record (EHR) data revealed a 114% increase in ED use among patients aged 80+ and a 11% decline among those aged 18-64 compared to the six-months prior ( 41 ). In addition to power outage-related care, this increase reflects spillover from other closed hospitals. In South Africa, Gehringer and colleagues evaluated repeated, daily, temporary outages on pediatric hospital admissions, finding an average treatment effect of 6 additional admissions per day due to any power outage in the two days prior ( 30 ). They found the largest effect sizes for respiratory outcomes, burns, and ear, eye, and gastrointestinal system outcomes in models that controlled for important factors like weather and seasonal and long-term trends.

Gastrointestinal illness.

Power outages can affect food refrigeration and water system supply and disinfection, potentially precipitating gastrointestinal illness as measured via poison control calls, prescription orders, and hospital admissions ( 30 , 45 , 48 , 78 ). However, evidence is mixed, with several studies finding no increase in gastrointestinal illness after power outages ( 72 , 78 , 86 ). Marx et al. employed methods from digital epidemiology to evaluate diarrheal illness after the 2003 Northeast Blackout finding that diarrheal syndrome ED visits, antidiarrheal medication sales, electrolyte sales, and worker absenteeism due to gastrointestinal illness all increased above expected in the days following the blackout ( 48 ).

Temperature-related illness.

Power outages reduce individuals’ ability to control the indoor environment and may coincide with temperature extremes (both heatwaves and winter storms) resulting in illness ( 40 , 42 , 51 , 53 , 55 , 68 , 77 , 80 ) and disturbed sleep ( 49 ) related to heat and cold exposure. Racial, socioeconomic, and age disparities exist in response to extreme temperature exposures, owing to differences including baseline health, access to generators, the urban heat island effect, and occupation ( 93 , 94 ).

Maternal and neonatal health.

Four studies assessed the relationship between power outages and maternal healthcare utilization, measures of fertility, and birthweight ( 73 , 74 , 79 , 83 ). Using monthly power outage data from 2010–2015 in India’s Maharashtra state, Koroglu and colleagues evaluated the relationship between SAIFI (system average interruption frequency index) and SAIDI (duration) metrics and use of maternal health services ( 83 ). Increased monthly SAIFI but not SAIDI was associated with reduced odds of delivering in a healthcare institution (versus at home), both indices were associated with reduced odds of attendance of birth by skilled professional, and neither were related to caesarean section delivery. Outages may affect a woman’s ability to travel to a healthcare facility or reduce her perception of the quality of care she will receive there, encouraging her to stay at home.

Burlando exploited a month-long 2008 blackout that occurred on the island of Zanzibar, Tanzania to study both measures of fertility (counts of live births) and birth weight ( 73 , 74 ). The outage caused both a transitory negative income shock, with those who used electricity at work reporting a decrease in earnings and hours worked, and individuals to spend more time at home. With data from the island’s main maternity hospital (500-900 births per month), Burlando used a difference-in-differences strategy to estimate the effect of the power outage on fertility and birthweight by comparing outcomes among mothers living in shehias (communities) with and without any electrification exposed and unexposed to the blackout at different times during pregnancy. They found that the blackout was associated with a 17% increase in live births (253 additional births) 8-10 months later ( 73 ). The outage also appeared to reduce birthweights 7-10 months later, with the strongest associations among the lowest-percentile weights (e.g., 8 th -percentile weight was reduced by 2kg) ( 74 ).

Mental health and wellbeing.

Qualitative studies identified worry, anxiety, stress, and reduced wellbeing among individuals exposed to power outages, generally tied to concerns about disrupted heating, food, water supplies, and healthcare ( 75 , 82 ). In the acute setting, healthcare-seeking for mental health problems may actually decline, as was seen immediately after the 2003 Northeast Blackout in NYC ( 40 ). Therefore, alternative data, such as Twitter, may supply valuable information about population health during an outage ( 20 ). Li et al. found a sharp drop in Twitter sentiment (i.e., more negative tweets) in the first hour of a NYC power outage in 2019. Other studies have evaluated longer-term effects of power outages ( 56 , 79 , 84 ) In Ghana, University students who experienced power outages ≥4 times per week had significantly higher levels of anxiety as measured by the generalized anxiety disorder 7-item scale ( 84 ). After Hurricane Sandy, ED visits for mental health problems among pregnant women in New York increased gradually and peaked eight months later at a level 33% higher than expected based on data from prior and subsequent years ( 79 ).

Three studies identified increased mortality after the 2003 Northeast Blackout in New York City (NYC), which affected 8 million NYC residents ( 39 , 47 , 80 ). Anderson and Bell found increased accidental (+122%) and non-accidental (+25%) mortality controlling for important environmental confounding variables such as temperature, air pollutants, day-of-week, and seasonal and long-term trends ( 39 ). Dominianni and colleagues extended Anderson and Bell’s study to span major NYC blackouts in 1999, 2003, and 2006, as well as localized outages in 66 NYC electric-grid networks ( 80 ), finding significant associations between localized cold-weather, but not warm-weather, outages and all-cause and non-external mortality. Conversely, Imperato could not identify an effect of the 1977 NYC power outage on all-cause mortality as it coincided with and could not be disentangled from a heatwave ( 43 ). Other studies have tied power outage-related mortality to CO poisoning (see prior section), falls ( 55 , 62 ), fire ( 55 , 62 ), heat ( 85 ), and cold exposure ( 55 ).

Other outcomes.

Several studies reported increases in healthcare visits for burns, lacerations, or other injuries ( 40 , 42 , 50 , 68 , 77 ), but attributing these events to power outages, rather than co-occurring exposures such as housing damage or motor vehicle crashes has been difficult. Further, two studies reported reduced prescription refills during power outages ( 42 , 52 ) and one found no change ( 50 ). After Hurricane Maria power outages lasted months in Puerto Rico and prescription refills did not revert to normal levels even one-year later ( 52 ).

REVIEW SUMMARY AND RECOMMENDATIONS

Recent studies point to a relationship between power outages and adverse health outcomes among community residents. Most have assessed single, large-scale power outages without linking events directly to patient residential addresses. New work has used data from electric utilities ( 80 , 81 , 83 ) and social media ( 30 ) to more accurately capture the temporal and spatial extent of outages. Consistent evidence from >20 studies across a range of power outages from hurricanes to ice storms to earthquakes finds increased rates of CO poisoning during outages as individuals use alternative fuel sources, such a generators and charcoal. We also observed moderate evidence for an association between power outages and all-cause, cardiovascular, respiratory, and renal disease hospitalizations, except for the sub-group of individuals relying on electricity-dependent medical equipment where associations consistently pointed to elevated risk. In times and places where power outages corresponded to hot or cold ambient temperatures, we found moderate evidence of a relationship between power outage and temperature-related illness, gastrointestinal illness, and mortality. Recent studies have broadened their scope to consider additional outcomes such as mental health ( 19 ), maternal and child health ( 73 , 74 , 83 ), prescription refills ( 42 , 52 ), and injuries ( 40 , 42 , 50 , 68 , 77 ); future work should continue to explore these and other potentially important outcomes.

Future areas for exposure assessment.

To date, most studies have focused on single power outages, which can allow better characterization of co-exposures but misses the larger burden of repeated outages and under-estimates individual-level effects. Studies should consider factors such as duration (e.g., longer outages are likely much worse for health) and location (e.g., outages in San Diego likely have fewer impacts than outages in Maine in the winter). The lack of resolved spatial and temporal exposure data has also limited research. Attribution of adverse health outcomes directly to power outages will require exploiting variability in power outage locations, times, duration, and severity among populations. Zhang et al. successfully did this using NYSPS data ( 81 ). Such data are difficult to acquire and do not exist for many regions of the U.S. and world. Therefore, borrowing from digital epidemiology ( 95 ), alternative strategies may be used, including remote sensing, internet connected devices, and social media, to characterize spatiotemporal variability in power outages.

Remote sensing.

Researchers can use satellite or aircraft to measure reflected and emitted radiation of the earth. In particular, remote sensing of artificial lights at night ( 96 ) can be used to measure power outages ( 97 ). In India, Min et al. created a Power Supply Irregularity (PSI) index using nighttime satellite imagery to compute the outage index in all 600,000 villages in India from 1993-2013 ( 97 ). Likewise, Román et al. used globally-available, daily nighttime light data from NASA’s Black Marble product to track electricity grid restoration in Puerto Rico after Hurricane Maria ( 32 ). These data were used to create three metrics down to 902 barrios: (1) percent recovery; (2) number of days without electricity; and (3) number of customer-hours of interruption.

Internet connected and other consumer devices.

Meier et al. used the power status of internet-connected thermostats, of which 6 million exist in the U.S., to track outages at 15-minute intervals during Hurricane Irma and severe windstorm ( 98 ). Others have proposed using smartphones ( 99 ) or a host of internet connected devices (e.g., alarm systems, ATM networks) to track power outages ( 100 ).

Social media.

Several researchers have used Twitter feeds to track power outages ( 20 , 101 - 104 ). One option is to use geotagged tweets ( 101 ), but these make up <1% of tweets as most users turn this function off ( 105 ). Instead, researchers can search for location-specific terms within tweets, for example, “New York City” or obtain information from registered locations from the users’ accounts ( 20 , 104 ). Khan et al. also attempted to extract power outage cause in four groups: manmade, natural (e.g., “storm”), wildlife, and faulty equipment ( 104 ). This type of data may have increased utility in the future.

Co-exposures/complex disasters:

One key and complicating feature of power outages is that they often occur alongside other disasters. Disentangling the impact of power outages from other physical destruction of infrastructure, such as landslides in Puerto Rico following Hurricane Maria ( 106 , 107 ), fuel crises in Nepal after the 2015 earthquake ( 108 ), or windstorms in Ohio following Hurricane Ike ( 109 ) may not be possible. Bromet et al. noted a synergistic effect of multiple Sandy-related exposures, where participants experiencing 3-5 exposures (i.e., loss of power, extreme concern about finding gasoline, filing a FEMA claim, extensive home damage, and extensive possession damage) had >6x the odds of PTSD and major depressive disorder compared to those experiencing 0 exposures ( 56 ). Many studies implicitly include power outage as an exposure, but the researchers do not explicitly cite power outage as the main exposure of interest. Future work should consider the long-tail, ancillary impact of power outage-related health effects. Sustained power outages result in delayed or interrupted access to healthcare from infrastructure damage, access limitations, inability to pay (from disaster-related impoverishment), and loss of personnel ( 34 , 83 , 110 ). Such deferred care, from delayed treatments, unfilled prescriptions, or failure of DMEs impacts morbidity and mortality–as was in the case after Hurricane Maria in Puerto Rico, where nearly 4000 excess deaths occurred ( 111 ).

Future areas for outcome assessment.

Outcome assessment should increase in depth and breadth. Most studies only evaluated immediate effects of power outages. Future studies should expand the timescale to assess outcomes in the short-term and long-term. For example, Xiao et al. defined immediate impacts of Hurricane Sandy as the 30-days after and long-term impacts over the following year ( 79 ). They found immediate and long-term increases in ED visits for overall pregnancy complications among women in eight Sandy-exposed New York counties that exceeded increases in 54 less-exposed counties, highlighting the need to extend the relevant follow-up period. While studies have begun to assess perinatal health, future work should also consider children, another susceptible group. Additionally, studies must continue to evaluate the health of older adults, who rely more heavily on electricity-dependent medical equipment ( 26 ) and may have cognitive impairment or functional limitations ( 112 ), increasing their vulnerability to power outages.

The use of large insurance claims databases or EHRs ( 113 ), combined with better exposure assessment, will allow for investigating the impact of power outages on health in at least three important ways. First, it will allow for assessing a larger variety of health outcomes over a longer period of time. Many outcomes, such as maternal and child health or mental health, are known to be sensitive to power outages, yet remained understudied. In addition to these outcomes, exploratory analyses of large claims databases may identify currently unknown outcomes impacted by power outages. Second, it will allow for identifying and studying particularly susceptible subpopulations, such as patients with temperature-sensitive co-morbidities like multiple sclerosis or heart failure. Lastly, it will allow for a more complete description of the racial/ethnic, socioeconomic, and spatially patterned disparities in health response to power outages. Very few studies to date employ spatial and temporal control groups, rigorous statistical methods, and assess for effect modification by import socioeconomic and racial/ethnic sub-groups. This work can assist in identifying crucial points of intervention to allow for equitable allocation of preparedness, response and recovery activities, and resources to reduce disparities.

Building resilience and supporting response.

Resiliency spans from the individual to regional and global levels and encompasses individual skills, community health, and societal resources ( 114 ).

Preparedness.

Individual and community preparedness, including access to alternative power sources, can influence the scope of effect of outages on population health. While baseline levels of individual preparedness appear low, a silver lining of repeated outages is that households become more prepared, buying additional supplies or equipment, over time ( 19 ). In Florida, CO poisoning counts increased after the first, but not the second or third consecutive hurricanes, suggesting increased awareness, preparedness, or public health warnings during subsequent hurricanes of the season ( 50 ). Personal preparedness can reduce the effect of power outages on health, but low socioeconomic status individuals have limited capacity to store food and water or own a generator ( 29 ) and marginalized groups may receive fewer disaster-related warnings ( 70 ). Instead, emergency planners should focus on bolstering community resilience–physical, economic, and social–which can take many forms, from strengthening infrastructure to reducing baseline environmental exposure levels and socioeconomic inequities to expanding social capacities ( 21 , 75 ). Resilient communities deploy collective strategies such as community kitchens, checking on older adults, and providing each other with warmth, food, and shelter during outages ( 19 , 115 ). Government officials and utilities can further support health and safety by providing advanced warning of power outages as well as estimated duration once the outage has begun.

Electricity infrastructure.

Several steps can be taken to improve electricity grid resiliency and response. These might include better protection against cyber-attacks and tree maintenance ( 1 , 16 , 116 ), improved weather forecasting that allows utilities to prepare, decentralized power generation such as solar and battery storage ( 117 , 118 ), smart grid technologies like advanced metering infrastructure and isolation and service restoration to update and enhance grid reliability ( 1 , 15 ). Rather than increase access to generators, modest system upgrades could also allow for low-amperage service (e.g., 20A, which would keep lights or air conditioning on) during outages, possibly paid for via monthly backup insurance payments of <$1 per customer ( 119 ).

Supporting health during outages.

In addition to primary prevention and building resilience, some specific actions can directly support power outage-related health maintenance. For example, notifying patients pre-disaster to refill prescriptions. Prior to a mid-Atlantic blizzard CVS pharmacy randomly notified 2.2 million patients to check their medication supply and found that they had a 9% increased odds of a refill within 48 hours compared to the comparison group ( 120 ). Pre-dialysis and other forms of pre-care at healthcare facilities can allow individuals to go safely without power for longer ( 121 ). We also must further identify locations and co-morbidities among those reliant on electricity-dependent medical equipment via patient registration with utility companies and information from EHRs or publicly-available data sources like the emPOWER mapping tool ( 25 , 26 , 122 ), and provide community-based charging stations for medical equipment. In North Carolina, >95% of severe CO poisoning after an ice storm occurred in households without CO detectors ( 123 ). The benefit-to-cost ratio of installing a CO monitor may be as high as 7.2 to 1 ( 124 ). Low-tech interventions, like paired CO monitor and generator purchases, or engineering controls like automatic generator shutoffs, low CO generators, or simply longer generator cords could reduce CO poisoning ( 125 ). Finally, in low-resource settings where outages can limit ability to travel to hospitals or results in blackouts at hospitals themselves, mobile clinics can offer distributed access to care ( 126 ) and novel technologies, like solar and storage or oxygen reservoir systems, can support further continuity of care ( 127 , 128 ).

As power outages increase in frequency and duration, researchers must expand efforts to understand their impact on individual and population health, refining methods of exposure assessment with attention to varied and disparate outcomes. There is urgent need for these data to inform disaster mitigation, preparedness and response policies (and budgets) in an increasingly energy-reliant world.

Recommendations for future exposure measurement and outcome assessment

Supplementary Material

40572_2020_295_moesm1_esm, acknowledgments.

FUNDING : Dr. Casey received funding from a National Institutes of Environmental Health Sciences R00 ES027023 and NIEHS P30 ES009089. Dr. Kiang received funding from National Institute on Drug Abuse K99 DA051534.

Conflict of interest : Joan A. Casey, Mihoka Fukurai, Diana Hernández, Satchit Balsari, and Mathew Kiang declare that they have no conflict of interest.

Human and Animal Rights : All reported studies/experiments with human or animal subjects performed by the authors have been previously published and complied with all applicable ethical standards (including the Helsinki declaration and its amendments, institutional/national research committee standards, and international/national/institutional guidelines).

Papers of particular interest, published in the past 3 years, have been highlighted as:

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Power Outages and Community Health: a Narrative Review

• Environmental Disasters (D Sandler and A Miller, Section Editors)
• Published: 11 November 2020
• Volume 7 , pages 371–383, ( 2020 )

Cite this article

• Joan A. Casey   ORCID: orcid.org/0000-0002-9809-4695 1 ,
• Mihoka Fukurai 2 ,
• Diana Hernández 3 ,
• Satchit Balsari 4 , 5 &
• Mathew V. Kiang 5 , 6  

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Purpose of Review

Power outages, a common and underappreciated consequence of natural disasters, are increasing in number and severity due to climate change and aging electricity grids. This narrative review synthesizes the literature on power outages and health in communities.

Recent Findings

We searched Google Scholar and PubMed for English language studies with titles or abstracts containing “power outage” or “blackout.” We limited papers to those that explicitly mentioned power outages or blackouts as the exposure of interest for health outcomes among individuals living in the community. We also used the reference list of these studies to identify additional studies. The final sample included 50 articles published between 2004 and 2020, with 17 (34%) appearing between 2016 and 2020. Exposure assessment remains basic and inconsistent, with 43 (86%) of studies evaluating single, large-scale power outages. Few studies used spatial and temporal control groups to assess changes in health outcomes attributable to power outages. Recent research linked data from electricity providers on power outages in space and time and included factors such as number of customers affected and duration to estimate exposure.

The existing literature suggests that power outages have important health consequences ranging from carbon monoxide poisoning, temperature-related illness, gastrointestinal illness, and mortality to all-cause, cardiovascular, respiratory, and renal disease hospitalizations, especially for individuals relying on electricity-dependent medical equipment. Nonetheless the studies are limited, and more work is needed to better define and capture the relevant exposures and outcomes. Studies should consider modifying factors such as socioeconomic and other vulnerabilities as well as how community resiliency can minimize the adverse impacts of widespread major power outages.

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Haes Alhelou H, Hamedani-Golshan ME, Njenda TC, Siano P. A survey on power system blackout and cascading events: research motivations and challenges. Energies. 2019;12(4):682.

Google Scholar  

Küfeoğlu S, Prittinen S, Lehtonen M. A summary of the recent extreme weather events and their impacts on electricity. Int Rev Electr Eng. 2014;9(4):821–8.

Matthewman S, Byrd H. Blackouts: a sociology of electrical power failure. Social Space (Przestrzeń Społeczna). 2013:31–55.

Auffhammer M, Baylis P, Hausman CH. Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States. Proc Natl Acad Sci U S A. 2017;114(8):1886–91.

CAS   PubMed   PubMed Central   Google Scholar  

Horton R, Rosenzweig C, Gornitz V, Bader D, O’Grady M. Climate risk information: climate change scenarios & implications for NYC infrastructure New York City panel on climate change. Ann N Y Acad Sci. 2010;1196(1):147–228.

PubMed   Google Scholar  

Pachauri RK, Allen MR, Barros VR, Broome J, Cramer W, Christ R, et al. Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change: IPCC; 2014.

The World Bank. Power Outages in Firms in a Typical Month 2020. Available from: https://data.worldbank.org/indicator/IC.ELC.OUTG . Accessed 4 Aug 2020.

Laghari J, Mokhlis H, Bakar A, Mohamad H. Application of computational intelligence techniques for load shedding in power systems: a review. Energy Convers Manag. 2013;75:130–40.

U.S. Energy Information Administration. EIA projects less than a quarter of the world’s electricity generated from coal by 2050. 2020 Available from: https://www.eia.gov/todayinenergy/detail.php?id=42555 . Accessed 29 Jul 2020.

Mukherjee S, Nateghi R, Hastak M. Data on major power outage events in the continental. US Data Brief. 2018;19:2079–83.

U.S. Energy Information Administration. Average U.S. electricity customer interruptions totaled nearly 8 hours in 2017. 2018. Available from: https://www.eia.gov/todayinenergy/detail.php?id=37652 . Accessed 4 June 2019.

Kenward A, Raja U. Blackout: Extreme weather, climate change, and power outages. Princeton; 2014.

U.S. Department of Energy. OE-417: Electric Emergency Incident and Disturbance Report. Available from: https://www.oe.netl.doe.gov/OE417/ . Accessed 10 Aug 2020.

Hines P, Apt J, Talukdar S. Large blackouts in North America: historical trends and policy implications. Energ Policy. 2009;37(12):5249–59.

Eaton. Blackout Tracker United States Annual Report 2018. United States; 2019.

The President’s National Infrastructure Advisory Council. Surviving a catastrophic power outage: how to strengthen the capabilities of the nation 2018. Available from: https://www.cisa.gov/publication/niac-catastrophic-power-outage-study . Accessed 31 Jul 2020.

Eto J. Final report on the August 14, 2003 blackout in the United States and Canada: causes and recommendations. Washington, DC: US-Canada Power System Outage Task Force; 2004.

Aon Benfield. Hurricane Sandy Event Recap Report: Impact Forecasting. Available from: http://thoughtleadership.aonbenfield.com/Documents/20130514_if_hurricane_sandy_event_recap.pdf . Accessed 14 Aug 2020.

Rubin GJ, Rogers MB. Behavioural and psychological responses of the public during a major power outage: a literature review. Int J Disaster Risk Reduct. 2019;101226.

• Li L, Ma Z, Cao T. Leveraging social media data to study the community resilience of New York City to 2019 power outage. Int J Disaster Risk Reduct. 2020:101776 This study illustrated the utility of using Twitter data to track psychosocial stress during and after power outages .

Chakalian PM, Kurtz LC, Hondula DM. After the lights go out: household resilience to electrical grid failure following hurricane Irma. Nat Hazards Rev. 2019;20(4):05019001.

Lemieux F. The impact of a natural disaster on altruistic behaviour and crime. Disasters. 2014;38(3):483–99.

Klinger C, Landeg O, Murray V. Power outages, extreme events and health: a systematic review of the literature from 2011-2012. PLoS Curr. 2014;6.

Bean R, Snow S, Glencross M, Viller S, Horrocks N. Keeping the power on to home medical devices. PLoS One. 2020;15(7):e0235068.

Molinari NA, Chen B, Krishna N, Morris T. Who’s at risk when the power goes out? The at-home electricity-dependent population in the United States, 2012. J Public Health Manag Pract. 2017;23(2):152–9.

PubMed   PubMed Central   Google Scholar  

Casey JA, Mango M, Mullendore S, Kiang MV, Hernández D, Li BH, et al. Trends from 2008–2018 in electricity-dependent durable medical equipment rentals and sociodemographic disparities. Under Rev. 2020.

Bethel JW, Foreman AN, Burke SC. Disaster preparedness among medically vulnerable populations. Am J Prev Med. 2011;40(2):139–43.

Cox K, Kim B. Race and income disparities in disaster preparedness in old age. J Gerontol Soc Work. 2018;61(7):719–34.

Dominianni C, Ahmed M, Johnson S, Blum M, Ito K, Lane K. Power outage preparedness and concern among vulnerable New York City residents. J Urban Health. 2018;95(5):716–26.

•• Gehringer C, Rode H, Schomaker M. The effect of electrical load shedding on pediatric hospital admissions in South Africa. Epidemiology. 2018;29(6):841–7 Identified power outages using a combination of social media and government data and applied causal inference methods to estimate the public health-relevant average treatment effect.

Liévanos RS, Horne C. Unequal resilience: the duration of electricity outages. Energ Policy. 2017;108:201–11.

Roman MO, Stokes EC, Shrestha R, Wang Z, Schultz L, Carlo EAS, et al. Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria. PLoS One. 2019;14(6):e0218883.

Yabe T, Ukkusuri SV. Effects of income inequality on evacuation, reentry and segregation after disasters. Transp Res D Transp Environ. 2020;82:102260.

Burger J, Gochfeld M, Lacy C. Ethnic differences in risk: experiences, medical needs, and access to care after hurricane Sandy in New Jersey. J Toxicol Environ Health A. 2019;82(2):128–41.

Jessel S, Sawyer S, Hernandez D. Energy, poverty, and health in climate change: a comprehensive review of an emerging literature. Front Public Health. 2019;7:357.

Irwin BR, Hoxha K, Grépin KA. Conceptualising the effect of access to electricity on health in low- and middle-income countries: a systematic review. Glob Public Health. 2020;15(3):452–73.

Adair-Rohani H, Zukor K, Bonjour S, Wilburn S, Kuesel AC, Hebert R, et al. Limited electricity access in health facilities of sub-Saharan Africa: a systematic review of data on electricity access, sources, and reliability. Glob Health Sci Pract. 2013;1(2):249–61.

Chawla S, Kurani S, Wren SM, Stewart B, Burnham G, Kushner A, et al. Electricity and generator availability in LMIC hospitals: improving access to safe surgery. J Surg Res. 2018;223:136–41.

Anderson GB, Bell ML. Lights out: impact of the August 2003 power outage on mortality in New York, NY. Epidemiology. 2012;23(2):189–93.

Freese J, Richmond NJ, Silverman RA, Braun J, Kaufman BJ, Clair J. Impact of a citywide blackout on an urban emergency medical services system. Prehosp Disaster Med. 2006;21(6):372–8.

Gotanda H, Fogel J, Husk G, Levine JM, Peterson M, Baumlin K, et al. Hurricane Sandy: impact on emergency department and hospital utilization by older adults in Lower Manhattan, New York (USA). Prehosp Disaster Med. 2015;30(5):496–502.

Greenstein J, Chacko J, Ardolic B, Berwald N. Impact of Hurricane Sandy on the Staten Island University hospital emergency department. Prehosp Disaster Med. 2016;31(3):335–9.

Imperato PJ. Public health concerns associated with the New York City blackout of 1977. J Community Health. 2016;41(4):707–16.

Johnson-Arbor KK, Quental AS, Li D. A comparison of carbon monoxide exposures after snowstorms and power outages. Am J Prev Med. 2014;46(5):481–6.

Klein KR, Herzog P, Smolinske S, White SR. Demand for poison control center services "surged" during the 2003 blackout. Clin Toxicol. 2007;45(3):248–54.

Kobayashi S, Hanagama M, Yamanda S, Satoh H, Tokuda S, Kobayashi M, et al. Impact of a large-scale natural disaster on patients with chronic obstructive pulmonary disease: the aftermath of the 2011 Great East Japan Earthquake. Respir Investig. 2013;51(1):17–23.

Lin S, Fletcher BA, Luo M, Chinery R, Hwang SA. Health impact in New York City during the northeastern blackout of 2003. Public Health Rep. 2011;126(3):384–93.

Marx MA, Rodriguez CV, Greenko J, Das D, Heffernan R, Karpati AM, et al. Diarrheal illness detected through syndromic surveillance after a massive power outage: New York City, August 2003. Am J Public Health. 2006;96(3):547–53.

Mizuno K, Okamoto-Mizuno K. Actigraphically evaluated sleep on the days surrounding the Great East Japan Earthquake. Nat Hazards. 2014;72(2):969–81.

Platz E, Cooper HP, Silvestri S, Siebert CF. The impact of a series of hurricanes on the visits to two Central Florida emergency departments. J Emerg Med. 2007;33(1):39–46.

Rand DA, Mener DJ, Lerner EB, DeRobertis N. The effect of an 18-hour electrical power outage on an urban emergency medical services system. Prehosp Emerg Care. 2005;9(4):391–7.

• Smith JY, Sow MM. Access to e-prescriptions and related technologies before and after Hurricanes Harvey, Irma, and Maria. Health Aff (Millwood). 2019;38(2):205–11 This retrospective study used a U.S. national health information network that transmits 1.7 billion e-prescriptions annually to assess the relationship between Hurricanes Harvey, Irma, and Maria and changes in provider prescribing activity.

Kearns RD, Wigal MS, Fernandez A, Tucker MA Jr, Zuidgeest GR, Mills MR, et al. The 2012 derecho: emergency medical services and hospital response. Prehosp Disaster Med. 2014;29(5):542–5.

Audin C. Carbon monoxide poisoning following a natural disaster: a report on Hurricane Rita. J Emerg Nurs. 2006;32(5):409–11.

Broder J, Mehrotra A, Tintinalli J. Injuries from the 2002 North Carolina ice storm, and strategies for prevention. Injury. 2005;36(1):21–6.

Bromet EJ, Clouston S, Gonzalez A, Kotov R, Guerrera KM, Luft BJ. Hurricane Sandy exposure and the mental health of World Trade Center responders. J Trauma Stress. 2017;30(2):107–14.

Cukor J, Restuccia M. Carbon monoxide poisoning during natural disasters: the Hurricane Rita experience. J Emerg Med. 2007;33(3):261–4.

Falise AM, Griffin I, Fernandez D, Rodriguez X, Moore E, Barrera A, et al. Carbon monoxide poisoning in Miami-Dade County following Hurricane Irma in 2017. Disaster Med Public Health Prep. 2019;13(1):94–6.

Fife CE, Smith LA, Maus EA, McCarthy JJ, Koehler MZ, Hawkins T, et al. Dying to play video games: carbon monoxide poisoning from electrical generators used after hurricane Ike. Pediatrics. 2009;123(6):e1035–8.

Gulati RK, Kwan-Gett T, Hampson NB, Baer A, Shusterman D, Shandro JR, et al. Carbon monoxide epidemic among immigrant populations: King County, Washington, 2006. Am J Public Health. 2009;99(9):1687–92.

Iseki K, Hayashida A, Shikama Y, Goto K, Tase C. An outbreak of carbon monoxide poisoning in Yamagata Prefecture following the Great East Japan Earthquake. Asia Pac J Med Toxicol. 2013;2(2):37–41.

Jani AA, Fierro M, Kiser S, Ayala-Simms V, Darby DH, Juenker S, et al. Hurricane Isabel-related mortality—Virginia, 2003. J Public Health Manag Pract. 2006;12(1):97–102.

Kile JC, Skowronski S, Miller MD, Reissman SG, Balaban V, Klomp RW, et al. Impact of 2003 power outages on public health and emergency response. Prehosp Disaster Med. 2005;20(2):93–7.

Klein JG, Alter SM, Paley RJ, Hughes PG, Clayton LM, Benda W, et al. Carbon monoxide poisoning at a Florida Hospital following Hurricane Irma. Am J Emerg Med. 2019;37(9):1800–1.

Lutterloh EC, Iqbal S, Clower JH, Spiller HA, Riggs MA, Sugg TJ, et al. Carbon monoxide poisoning after an ice storm in Kentucky, 2009. Public Health Rep. 2011;126(Suppl 1):108–15.

Muscatiello NA, Babcock G, Jones R, Horn E, Hwang SA. Hospital emergency department visits for carbon monoxide poisoning following an October 2006 snowstorm in western New York. J Environ Health. 2010;72(6):43–8.

Nakayama T, Tanaka S, Uematsu M, Kikuchi A, Hino-Fukuyo N, Morimoto T, et al. Effect of a blackout in pediatric patients with home medical devices during the 2011 eastern Japan earthquake. Brain Dev. 2014;36(2):143–7.

Prezant DJ, Clair J, Belyaev S, Alleyne D, Banauch GI, Davitt M, et al. Effects of the August 2003 blackout on the New York City healthcare delivery system: a lesson for disaster preparedness. Crit Care Med. 2005;33(1 Suppl):S96–101.

Schnall A, Law R, Heinzerling A, Sircar K, Damon S, Yip F, et al. Characterization of carbon monoxide exposure during Hurricane Sandy and subsequent Nor'easter. Disaster Med Public Health Prep. 2017;11(5):562–7.

Styles T, Przysiecki P, Archambault G, Sosa L, Toal B, Magri J, et al. Two storm-related carbon monoxide poisoning outbreaks-Connecticut, October 2011 and October 2012. Arch Environ Occup Health. 2015;70(5):291–6.

Van Sickle D, Chertow DS, Schulte JM, Ferdinands JM, Patel PS, Johnson DR, et al. Carbon monoxide poisoning in Florida during the 2004 hurricane season. Am J Prev Med. 2007;32(4):340–6.

Baer A, Elbert Y, Burkom HS, Holtry R, Lombardo JS, Duchin JS. Usefulness of syndromic data sources for investigating morbidity resulting from a severe weather event. Disaster Med Public Health Prep. 2011;5(1):37–45.

Burlando A. Power outages, power externalities, and baby booms. Demography. 2014;51(4):1477–500.

Burlando A. Transitory shocks and birth weights: evidence from a blackout in Zanzibar. J Dev Econ. 2014;108:154–68.

Moreno J, Shaw D. Community resilience to power outages after disaster: a case study of the 2010 Chile earthquake and tsunami. Int J Disaster Risk Reduct. 2019;34:448–58.

• Nakajima M, Aso S, Matsui H, Fushimi K, Yamaguchi Y, Yasunaga H. Disaster-related carbon monoxide poisoning after the Great East Japan Earthquake, 2011: a nationwide observational study. Acute Med Surg. 2019;6(3):294–300 This study used an inpatient database to compare counts carbon monoxide poisoning before and after among disaster-exposed and unexposed regions following the 2011 Japanese Earthquake.

Rajaram N, Hohenadel K, Gattoni L, Khan Y, Birk-Urovitz E, Li L, et al. Assessing health impacts of the December 2013 ice storm in Ontario, Canada. BMC Public Health. 2016;16:544.

Pirard P, Goria S, Nguengang Wakap S, Galey C, Motreff Y, Guillet A, et al. No increase in drug dispensing for acute gastroenteritis after Storm Klaus, France 2009. J Water Health. 2015;13(3):737–45.

CAS   PubMed   Google Scholar  

•• Xiao J, Huang M, Zhang W, Rosenblum A, Ma W, Meng X, et al. The immediate and lasting impact of Hurricane Sandy on pregnancy complications in eight affected counties of New York State. Sci Total Environ. 2019;678:755–60 This time-series study used database contained 95% of New York hospitalizations and finds evidence of increased acute and chronic ED visits for pregnancy complications after Hurricane Sandy.

•• Dominianni C, Lane K, Johnson S, Ito K, Matte T. Health impacts of citywide and localized power outages in New York City. Environ Health Perspect. 2018;126(6):067003 Evaluated both large single outages and localized power outage in NYC and differentiated between warm- and cold-season power outages.

•• Zhang W, Sheridan SC, Birkhead GS, Croft DP, Brotzge J, Justino JG, et al. Power Outage: an ignored risk factor for COPD exacerbations. Chest. 2020; This retrospective cohort study assigned power outages by power-operating divisions in New York state from 2001–2013 and used distributed lag nonlinear models controlling for time-varying confounders.

Amadi HN. Impact of power outages on developing countries: evidence from rural households in Niger Delta, Nigeria. J Energy Resour Technol. 2015;5(3):27–38.

• Koroglu M, Irwin BR, Grépin KA. Effect of power outages on the use of maternal health services: evidence from Maharashtra, India. BMJ Glob Health. 2019;4(3):e001372 Data on SAIDI and SAIFI values from India’s largest distribution utility revealed a relationship between power outages and maternal healthcare.

Ibrahim A, Aryeetey GC, Asampong E, Dwomoh D, Nonvignon J. Erratic electricity supply (Dumsor) and anxiety disorders among university students in Ghana: a cross sectional study. Int J Ment Heal Syst. 2016;10:17.

Stoppacher R, Yancon AR, Jumbelic MI. Fatalities associated with the termination of electrical services. Am J Forensic Med Pathol. 2008;29(3):231–4.

Cox R, Amundson T, Brackin B. Evaluation of the patterns of potentially toxic exposures in Mississippi following hurricane Katrina. Clin Toxicol. 2008;46(8):722–7.

Hampson NB, Stock AL. Storm-related carbon monoxide poisoning: lessons learned from recent epidemics. Undersea Hyperb Med. 2006;33(4):257–63.

Iqbal S, Clower JH, Hernandez SA, Damon SA, Yip FY. A review of disaster-related carbon monoxide poisoning: surveillance, epidemiology, and opportunities for prevention. Am J Public Health. 2012;102(10):1957–63.

Waite T, Murray V, Baker D. Carbon monoxide poisoning and flooding: changes in risk before, during and after flooding require appropriate public health interventions. PLoS Curr. 2014;6.

Rose JJ, Wang L, Xu Q, McTiernan CF, Shiva S, Tejero J, et al. Carbon monoxide poisoning: pathogenesis, management, and future directions of therapy. Am J Respir Crit Care Med. 2017;195(5):596–606.

Pages B, Planton M, Buys S, Lemesle B, Birmes P, Barbeau EJ, et al. Neuropsychological outcome after carbon monoxide exposure following a storm: a case-control study. BMC Neurol. 2014;14:153.

Greenwald PW, Rutherford AF, Green RA, Giglio J. Emergency department visits for home medical device failure during the 2003 North America blackout. Acad Emerg Med. 2004;11(7):786–9.

Gronlund CJ. Racial and socioeconomic disparities in heat-related health effects and their mechanisms: a review. Curr Epidemiol Rep. 2014;1(3):165–73.

Song X, Wang S, Hu Y, Yue M, Zhang T, Liu Y, et al. Impact of ambient temperature on morbidity and mortality: an overview of reviews. Sci Total Environ. 2017;586:241–54.

Salathe M, Bengtsson L, Bodnar TJ, Brewer DD, Brownstein JS, Buckee C, et al. Digital epidemiology. PLoS Comput Biol. 2012;8(7):e1002616.

Levin N, Kyba CCM, Zhang Q, Sánchez de Miguel A, Román MO, Li X, et al. Remote sensing of night lights: A review and an outlook for the future. Remote Sens Environ. 2020;237:111443.

Min B, O'Keeffe Z, Zhang F. Whose power gets cut? Using high-frequency satellite images to measure power supply irregularity: the World Bank; 2017.

Meier A, Ueno T, Pritoni M. Using data from connected thermostats to track large power outages in the United States. Appl Energy. 2019;256:113940.

Klugman N, Rosa J, Pannuto P, Podolsky M, Huang W, Dutta P, editors. Grid watch: Mapping blackouts with smart phones. Proceedings of the 15th Workshop on Mobile Computing Systems and Applications; 2014.

Simoes J, Blanquet A, Santos N, editors. Near real-time outage detection with spatio-temporal event correlation. CIRED Workshop 2016; 2016: IET.

Hultquist C, Simpson M, Cervone G, Huang Q. Using nightlight remote sensing imagery and Twitter data to study power outages. Proceedings of the 1st ACM SIGSPATIAL International Workshop on the Use of GIS in Emergency Management; Bellevue, Washington: Association for Computing Machinery; 2015. p. Article 6.

Mao H, Thakur G, Sparks K, Sanyal J, Bhaduri B. Mapping near-real-time power outages from social media. Int J Digit Earth. 2019;12(11):1285–99.

Sun H, Wang Z, Wang J, Huang Z, Carrington N, Liao J. Data-driven power outage detection by social sensors. IEEE Trans Smart Grid. 2016;7(5):2516–24.

Khan SS, Wei J, editors. Real-time power outage detection system using social sensing and neural networks. 2018 IEEE global conference on signal and information processing (GlobalSIP); 2018 26–29.

Huang B, Carley KM, editors. A large-scale empirical study of geotagging behavior on twitter. Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining; 2019.

Bessette-Kirton EK, Cerovski-Darriau C, Schulz WH, Coe JA, Kean JW, Godt JW, et al. Landslides triggered by Hurricane Maria: assessment of an extreme event in Puerto Rico. GSA Today. 2019;29(6):4–10.

Van Beusekom AE, Álvarez-Berríos NL, Gould WA, Quiñones M, González G. Hurricane Maria in the US Caribbean: disturbance forces, variation of effects, and implications for future storms. Remote Sens. 2018;10(9):1386.

Adhikari B, Mishra SR, Sujan Babu M, Kaehler N, Paudel K, Adhikari J, et al. Earthquakes, fuel crisis, power outages, and health care in Nepal: implications for the future. Disaster Med Public Health Prep. 2017;11(5):625–32.

Schmidlin TW. Public health consequences of the 2008 Hurricane Ike windstorm in Ohio, USA. Nat Hazards. 2011;58(1):235–49.

Ochi S, Leppold C, Kato S. Impacts of the 2011 Fukushima nuclear disaster on healthcare facilities: a systematic literature review. Int J Disaster Risk Reduct. 2020;42:101350.

Kishore N, Marques D, Mahmud A, Kiang MV, Rodriguez I, Fuller A, et al. Mortality in Puerto Rico after Hurricane Maria. N Engl J Med. 2018;379(2):162–70.

Banks L. Caring for elderly adults during disasters: improving health outcomes and recovery. South Med J. 2013;106(1):94–8.

Casey JA, Schwartz BS, Stewart WF, Adler N. Using electronic health records for population health research: a review of methods and applications. Annu Rev Public Health. 2015;37:61–81.

The International Federation of Red Cross and Red Crescent Societies. IFRC Framework for Community Resilience Geneva 2014. Available from: https://media.ifrc.org/ifrc/wp-content/uploads/sites/5/2018/03/IFRC-Framework-for-Community-Resilience-EN-LR.pdf . Accessed 29 Aug 2020.

Helsloot I, Beerens R. Citizens' response to a large electrical power outage in the Netherlands in 2007. J Conting Crisis Manag. 2009;17(1):64–8.

Parent JR, Meyer TH, Volin JC, Fahey RT, Witharana C. An analysis of enhanced tree trimming effectiveness on reducing power outages. J Environ Manag. 2019;241:397–406.

Robinson M, Shapiro A. Home Healthcare in the Dark: Clean Energy Group and Meridian Institute; 2019.

Rosales-Asensio E, de Simón-Martín M, Borge-Diez D, Blanes-Peiró JJ, Colmenar-Santos A. Microgrids with energy storage systems as a means to increase power resilience: an application to office buildings. Energy. 2019;172:1005–15.

Baik S, Morgan MG, Davis AL. Providing limited local electric service during a major grid outage: a first assessment based on customer willingness to pay. Risk Anal. 2018;38(2):272–82.

Lurie N, Bunton A, Grande K, Margolis G, Howell B, Shrank WH. A public-private partnership for proactive pharmacy-based outreach and acquisition of needed medication in advance of severe winter weather. JAMA Intern Med. 2017;177(2):271–2.

Miles SB, Jagielo N, Gallagher H. Hurricane Isaac power outage impacts and restoration. J Infrastruct Syst. 2016;22(1):05015005.

DeSalvo KB. The health consequences of natural disasters in the United States: progress, perils, and opportunity. Ann Intern Med. 2018;168(6):440–1.

Use of carbon monoxide alarms to prevent poisonings during a power outage--North Carolina, December 2002. MMWR Morb Mortal Wkly Rep. 2004;53(9):189–92.

Ran T, Nurmagambetov T, Sircar K. Economic implications of unintentional carbon monoxide poisoning in the United States and the cost and benefit of CO detectors. Am J Emerg Med. 2018;36(3):414–9.

Henretig FM, Calello DP, Burns MM, O'Donnell KA, Osterhoudt KC. Predictable, preventable, and deadly: epidemic carbon monoxide poisoning after storms. Am J Public Health. 2018;108(10):1320–1.

Neke NM, Gadau G, Wasem J. Policy makers’ perspective on the provision of maternal health services via mobile health clinics in Tanzania-findings from key informant interviews. PLoS One. 2018;13(9):e0203588.

Calderon R, Morgan MC, Kuiper M, Nambuya H, Wangwe N, Somoskovi A, et al. Assessment of a storage system to deliver uninterrupted therapeutic oxygen during power outages in resource-limited settings. PLoS One. 2019;14(2):e0211027.

Hawkes MT, Conroy AL, Namasopo S, Bhargava R, Kain KC, Mian Q, et al. Solar-oowered oxygen delivery in low-resource settings: a randomized clinical noninferiority trial. JAMA Pediatr. 2018;172(7):694–6.

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Dr. Casey received funding from a National Institutes of Environmental Health Sciences R00 ES027023 and NIEHS P30 ES009089. Dr. Kiang received funding from National Institute on Drug Abuse K99 DA051534.

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Casey, J.A., Fukurai, M., Hernández, D. et al. Power Outages and Community Health: a Narrative Review. Curr Envir Health Rpt 7 , 371–383 (2020). https://doi.org/10.1007/s40572-020-00295-0

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Understanding the social impacts of power outages in North America: a systematic review

Adam X Andresen 5,1 , Liza C Kurtz 2 , David M Hondula 3 , Sara Meerow 3 and Melanie Gall 4

Published 9 May 2023 • © 2023 The Author(s). Published by IOP Publishing Ltd Environmental Research Letters , Volume 18 , Number 5 Citation Adam X Andresen et al 2023 Environ. Res. Lett. 18 053004 DOI 10.1088/1748-9326/acc7b9

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1 Joseph R Biden Jr. School of Public Policy and Administration, Newark, DE 19716, United States of America

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As demand for electricity increases on an already strained electrical supply due to urbanization, population growth, and climate change, the likelihood of power outages will also increase. While researchers understand that the number of electrical grid disturbances is increasing, we do not adequately understand how increased power outages will affect a society that has become increasingly dependent on a reliable electric supply. This systematic review aims to understand how power outages have affected society, primarily through health impacts, and identify populations most vulnerable to power outages based on the conclusions from prior studies. Based on search parameters, 762 articles were initially identified, of which only 50 discussed the social impacts of power outages in North America. According to this literature, racial and ethnic minorities, especially Blacks or African Americans, those of lower socioeconomic status, children, older adults, and those living in rural areas experienced more significant impacts from previous power outages. Additionally, criminal activity increased during prolonged power outages with both pro-social and anti-social behaviors observed. Providing financial assistance or resources to replace spoiled goods can reduce crime. Future research on this topic must consider the financial effects of power outages, how power outage impacts seasonally vary, and the different durations of power outage impacts.

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1. Introduction

The most recent reports from the Intergovernmental Panel on Climate Change suggests that heat waves and deep freezes will increase demand for electricity which in turn will lead to brownouts—intentional or unintentional drops in voltage to conserve electricity during emergencies—and blackouts (Revi et al 2014 , Dodman et al 2022 ). Similarly, the 2021 American Society for Civil Engineers (ASCE) infrastructure report card rated the current condition of electrical infrastructure in the United States as mediocre, a slight improvement from the 2017 report. The report card defines mediocre as infrastructure in fair or good condition, but that requires attention and elements of the system show significant deficiencies in condition and functionality, thus increasing its vulnerability to risk (ASCE 2021 ). The ASCE estimated that more than 2.5 trillion dollars would be required to restore the nation's infrastructure to acceptable conditions (ASCE 2021 ). This frail and failing infrastructure will be further stressed by the effects of the changing climate, including more frequent anomalous weather events, as well as increasing population and associated demand for reliable electricity (Anderson and Bell 2012 , Matthewman and Byrd 2014 , USGCRP 2018). The current infrastructure was not designed to withstand the capacity of a rapidly increasing and urbanizing global population and is vulnerable due to outdated design standards (Chester and Allenby 2018 , 2019 ). The system, as designed, is highly interdependent with other critical systems, such as water purification and communication networks; any failures within the electrical system can lead to failures in other systems that depend on continuous electricity (Rinaldi et al 2001 ). As a result, scholars anticipate that the likelihood of blackouts, and their consequences, will increase in the coming decades (Anderson and Bell 2012 , Matthewman and Byrd 2014 , Burillo et al 2017 ). Infrastructure that is adaptive and flexible to the effects anticipated in the future climate is essential to mitigate impacts from future shocks and stressors (Chester and Allenby 2018 ). In this context, we are defining adaptive as having the capacity to respond to shocks and stressors to the system while maintaining its fitness (Chester and Allenby 2018 ). Future infrastructure design must consider all potential scenarios of the future climate and adapt infrastructure accordingly (Burillo et al 2017 ).

Recent large-scale failures in the electrical grid have also highlighted the critical nature of urgent infrastructure repairs. In 2019, the state of California experienced rolling blackouts to address an increasing wildfire threat. New York also experienced a brownout in 2020 that caused a widespread, and unexpected power outage. Most recently, in 2021, Texas experienced a near collapse of its electrical grid, leaving electricity providers to implement rolling blackouts that lasted for days in extremely cold temperatures. Recently passed legislation allocates funding into America's infrastructure systems over the next 10 years (The White House 2021 ). This investment in infrastructure provides a foundation to restore the infrastructure systems to acceptable conditions, but additional investments are needed to ensure that systems can still operate under future stresses and strains (ASCE 2021 ). While electrical grid failures are technological in nature, the impacts to human health and safety add a societal component to these technical failures.

People are affected adversely by power outages. Physical health impacts are a large concern during power outages, especially for those that rely on an electricity-dependent medical device (Miles et al 2014 , Miles and Jagielo 2014 , Esmalian et al 2019 ). Mental health issues also become a concern during power outages, as those affected are living in temporary uncertainty about how long the event will last and how it may affect them (Rubin and Rogers 2019 ). As these examples make clear, the effects of power outages are not uniform across society. Given the growing risks, it is important to understand how power outages may differentially impact various populations because of their unique social and household characteristics.

The purpose of this review is to understand how people are affected during power outages by utilizing 42 years (1978–2019) of academic literature. To the best of our knowledge, this is the first review that explores all social impacts of outages from literature published over a long time span. Klinger et al ( 2014 ), Rubin and Rogers ( 2019 ), and Casey et al ( 2020 ) conducted similar reviews. Klinger et al ( 2014 ) only focused on two years of peer-reviewed literature (2011–2012) and identified 20 relevant articles on the health impacts of power outages. They also utilized media pieces to further augment their analysis of power outages outside of North America (Klinger et al 2014 ). Casey et al ( 2020 ) also examined power outage impacts through a community health perspective. Rubin and Rogers ( 2019 ) focused on the psychological and behavioral impacts of power outages and argued that these concerns needed to be addressed by public leaders. Rubin & Rogers identified 47 articles in their review on how the public reacted to a major loss of electricity, did not have a geographic boundary, and included hypothetical, or what they call, "threatened" events. Our aim is to assess common themes in the literature on how different people are impacted by power outages. In short, this review advances knowledge by examining a broader range of social impacts.

These methodologies are similar to our review; however, we did not limit the scope to only health impacts, did not consider media pieces, and only used Scopus for our review and did not include Google Scholar or Web of Science. While we recognize Google Scholar and Web of Science are two common academic citation databases, each have their strengths and weaknesses over Scopus. Harzing and Alakangas ( 2016 ) found that Scopus yielded more results and the largest growth in the number of papers compared to Google Scholar and Web of Science. Google Scholar's interface does not allow for bibliometric analyses to be done and does not provide the same filtering options that Scopus provides (Harzing and Alakangas 2016 ). Google Scholar and Scopus have become as reliable, if not more than, Web of Science. We ultimately decided on Scopus to increase the probability of finding articles related to the topic of interest while also filtering out articles that would not be as relevant from Google Scholar (Harzing and Alakangas 2016 ).

When discussing the social impacts of power outages, we are considering the impacts to people and households that could occur during a power outage, regardless of how the outage occurred. We are defining social impacts as the direct and indirect effects on people's well-being or their physical or mental health. Some examples of direct impacts include being unable to use an electronic medical device and increased feelings of anxiety because of not knowing when power would be restored. Examples of indirect impacts are having thrown spoiled food away and re-locating temporarily to a location that has not lost power.

In the next section we detail the systematic review methodology, inclusion and exclusion criteria, and literature selected for this review. In section 3 , we present the findings from the literature categorized into common themes, accompanied by a discussion. Finally, in section 4 , we summarize these insights and propose future directions for power outage research.

2. Review methodology

2.1. literature search.

Roughly 20 preliminary searches were conducted to iteratively identify a set of search terms that would return articles relevant to the research objective (see table 1 for the searches used to create the list of results for this review). At first, we focused on using search terms that were relevant to identifying research related to power outages that occurred after a natural hazard. While reading through abstracts of previous searches, it was apparent that we were missing outages that occurred independently, or those that were initiated due to failures within the electric grid system itself. We revised our terms to include papers related to these events within our review. Ultimately, we used two separate keyword lists to build a set of candidate articles for inclusion, and evaluated articles on each list based on inclusion criteria. We searched for articles using Scopus, limiting the search to peer-reviewed literature articles published in English with the search terms present in the title, abstract, or keywords (Andresen 2020 ). We understand that papers may be missing from the Scopus database and our search criteria may not capture all relevant papers. There also might be relevant non-peer-reviewed work that is relevant to this topic but not included in our criteria. We acknowledge and recognize these aspects of the methodology as potential limitations (Harzing and Alakangas 2016 ). The first set of search terms, applied in December 2019, used 'power outage*' AND 'impact*'. This search yielded 513 candidate articles.

Table 1.  Search terms used to return the final list used for this systematic review (Andresen 2020 ). Reproduced from Andresen ( 2020 ) CC BY 4.0 .

The second set of search terms was applied in February 2020 to broaden the scope of articles on the social impacts of power outages that were included. The terms used in the searches, specifically power outage, blackout, and power failure, were used as they are similar in meaning and could most effectively capture research related to electricity disruptions. Excluding terms like alcohol and drink were necessary because in preliminary searches, there were instances where blackout would return results related to either medical conditions or over-consumption of alcohol, which is not the purpose of this review. Other terms, like electricity, were not included but should be considered when conducting future reviews on this topic; we recognize there are search terms that could yield additional articles to include in our review and acknowledge that omitting certain search terms as a limitation to our review. When examining the results from the first search, it appeared we were missing papers from the health perspective of power outages. The second search used a set of terms aimed at expanding the scope of the research further, by attempting to find relevant research from the health perspective, like that of Klinger et al ( 2014 ). The second search produced 560 articles.

We did not specifically examine research on modeling power outage patterns, both spatially and temporally, nor did we intend to review the findings of papers that explore the potential impacts that are modeled through simulations of future power outages, providing access to electricity, or maintaining a reliable electric supply. We also recognize that the infrastructure management in North America differs from other countries and that papers focused outside of North America were less likely to be written in English, and thus would have to be excluded per our filtering criteria. We also acknowledge that other languages are common within the United States, however the authors did not have the knowledge or resources available to accurately translate papers written in another language to include them in the review, and recognize this language barrier as a limitation to this review.

We bounded our review to only studies that focused on events within North America. We limited the geographic scope of papers in this review to North America due to aspects of the United States' electric grid existing in Canada and Mexico (Andresen 2020 ). Therefore, when failures occurr in the United States, the effects can, sometimes, cascade throughout portions of the system beyond the United States border. We did not limit the geographic scope to only the United States given this overlap with the two countries at certain points within the system (Learn More About Interconnections, n.d.).

2.2. Coding

The aforementioned search terms returned 762 results in Scopus. We read each abstract to determine if the paper possibly examined the social impacts of power outages. After reading through the abstracts the first time, four inductive and inclusive themes emerged: modeling ( n = 173), technical ( n = 393), social ( n = 70), and other ( n = 333). Abstracts were read a second time to classify each abstract into these themes. Papers classified as modeling used a simulation or modeling technique to simulate power outage occurrences. Those classified as technical papers explore the impacts of power outages on physical infrastructure. Social research examined impacts on individuals, households, or demonstrated how power outages impacted critical social services. The other category served as a classification for papers that do not fall under the three previously listed categories. Only those classified as social, either exclusively or in combination with other categories, were subject to additional criteria to determine if they examined the social impacts of power outages and were eligible for inclusion in the full review. This step eliminated 636 papers. As part of this screening, we excluded 125 papers that examined a significant weather event but did not detail the impacts of the ensuing power outage. We eliminated 391 papers that observed the impacts past power outages had, or future outages may have, on the electric grid or other aspects of the electrical grid system, classified as only a technical paper. We excluded studies that examined willingness-to-pay or discrete choice experiments and classified these studies as other. While these studies estimated the number of money people would consider paying to avoid outages, no connection to impacts was made (Carlsson and Martinsson 2008 , Abdullah and Mariel 2010 ). Additional studies excluded consisted of a biographical account of living in a situation with unreliable electricity outside of North America or deploying a model or simulation to show the potential impacts that could affect people (Hiete et al 2011 , Kesselring 2017 ). We also removed 19 duplicate entries and 30 papers that were inaccessible, not written in English, or had insufficient data in the Scopus search returns. We then read the full text of the remaining 77 articles. After the full-text read of each paper, 27 more papers were removed as they did not examine the social impacts of power outages, despite making it through the previous criteria; 50 papers remained. Finally, we removed ten papers focused on areas outside of North America resulting in a final dataset of 40 papers. The authors were aware of ten additional papers from previous work and papers that were not included in the search results, bringing the final total to 50 papers for this review. A visual depiction of this process is displayed in figure 1 . More details about the literature used can be found in the supplemental material.

Figure 1.  A visualization of the filtering process to obtain the list of literature used for this review. Adapted from Andresen ( 2020 ) CC BY 4.0 .

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We further analyzed the papers based on their research design and the methods used to conduct the research (see table 2 ). The research design and method themes emerged from the included papers based on the authors' descriptions and explanations. After categorizing the research designs for each paper included in the review, we classified the papers further to examine the common methodologies used to study the social impacts of power outages. The themes developed using an inductive approach to allow themes to emerge. This review did not use software to analyze the literature.

Table 2.  A list of events and their frequency in the literature reviewed. Adapted from Andresen ( 2020 ) CC BY 4.0 .

3. Results and discussion

3.1. descriptive and thematic analysis.

One of the most striking findings from our review is that only five percent of the original sample of 762 papers identified in Scopus focused on the social impacts of power outages. Of the 50 papers included in this review, six also included a statistical modeling component and were categorized as modeling. Four papers also discussed components of the hard infrastructure or the technical aspects of power outages and were also labeled technical. Finally, four papers also were classified as other as their methods or overall objective did not fit within the scope of a modeling or technical paper. Of the 50 papers analyzed, 40 solely focused on the social effects of power failures without addressing one or more of the other categories (see figure 2 ).

Figure 2.  A visual breakdown showing how many papers included in the review fell under each category. Adapted from Andresen ( 2020 ) CC BY 4.0 .

Significant events, like large-scale blackouts, provide an opportunity to research the social impacts of power outages; however, these are not planned events and can be difficult to anticipate for researchers. The primary focus of the literature we examined was the impact of power outages during the aftermath of significant weather or geological events. Most of the literature here focused on power outages lasting for more than one day (see table 2 ). From the 50 papers used in this review, 46 examined the power outage impacts of 26 distinct events. The most frequently examined events were the 2003 blackout that occurred across the northeastern United States and parts of Canada and Superstorm Sandy (2012), which were the subject of ten articles and seven articles, respectively. The 1977 blackout in New York City, Hurricane Irma (2017), and Hurricane Isaac (2012) were also each the subject of more than one article we reviewed; other events mentioned were examined in the literature only once. The remainder of the research did not emerge from a significant event ( n = 4).

We found that articles related to the social impacts of power failures appeared in 40 different journals (see table 3 ), suggesting that this research is highly interdisciplinary. Only five journals published more than one article included in this review. These journals included Prehospital and Disaster Medicine (five publications), Disaster Medicine and Public Health Preparedness (three publications), the Journal of Environmental Health, Natural Hazards, the American Journal of Preventive Medicine, and the Journal of Infrastructure Systems (each with two publications). Journal titles reflected a wide range of disciplines addressing the social impacts of power failure, including public health, geography, sustainability, and energy.

Table 3.  A list of journals, and frequencies, where articles for the review were published. Reproduced from Andresen ( 2020 ) CC BY 4.0 .

There has also been a rise in scholarship in this field over recent decades (figure 3 ). Before the 21st century, we found only four articles on the social impacts of power outages, with the earliest article in our review published in 1978, ten from 2000–2009, and 35 from 2010–2019. However, it should be noted that this increase may correspond to the overall increase in published research within the past decade, as well as opportunities for research presented by hazards such as Hurricane Isaac and Superstorm Sandy (2012), and Hurricanes Irma and Maria (2017). The possibility does exist that some events received more research attention in general and could therefore have more papers written about them, including those related to power outage impacts. However, examining which events have been studied most frequently in greater detail is outside the scope of this review.

Figure 3.  A line graph showing the frequency of papers published each year from 1978–2019. Adapted from Andresen ( 2020 ) CC BY 4.0 .

We further classified the papers we reviewed based on their design and methodological approach. Each paper was classified as either a case study or systematic literature review. If the paper was classified as a case study, we further classified the paper based on the method(s) used. The most common methods in the articles we reviewed were interviews ( n = 12), followed by surveys ( n = 7), reports or summaries of events ( n = 3), models ( n = 2), and other ( n = 1). To clarify, any research classified as a case study examined a variety of impacts because of an event but maintained a focus on the ensuing power outage that occurred after the event (see table 4 ).

Table 4.  A list of the designs and methods used throughout the review. Adapted from Andresen ( 2020 ) CC BY 4.0 .

As of June 2020, when we collected citation information, the papers found through this review were only modestly cited in the literature, with an average citation count of 10.84 citations per paper (standard deviation = 11.85). Forty-four of the 50 papers in this review were within one standard deviation of the average citation count. Forty-seven of the papers were within two standard deviations of the average. The most cited had, at the time of this review, 56 citations (Anderson and Bell 2012 ), with the next highest being 45 citations (Marx et al 2006 ), and then 40 citations (Greenwald et al 2004 ). Most of the papers published before 2000 have a relatively small number of citations, except for Wrenn and Conners ( 1997 ) with 30 citations.

3.2. Themes within the literature

This section encompasses the relevant findings from the literature across three inductive themes: populations of concern ( n = 29), health impacts ( n = 24), and criminal activity ( n = 6) (see also Andresen ( 2020 ) for more information about these results).

3.2.1. Health impacts

This section examines the 24 studies that observed the health impacts of previous power outages and how these events impacted healthcare systems. This section also highlights the physical and mental impacts to human health that were caused by power outages.

3.2.1.1. Physical health impacts

Health impacts were a common theme in the literature. One of the main concerns from the health sector when a major power outage occurs is the increase in the emergency department (ED) visits due to carbon monoxide (CO) poisoning. CO poisoning primarily resulted from improper and unsafe usage of generators during a power outage, as noted by Riddex and Dellgar ( 2001 ), Van Sickle et al ( 2007 ), Fife et al ( 2009 ), Call ( 2010 ) and Wrenn and Conners ( 1997 ). An increase in the number of hospital and ED admissions due to carbon monoxide was reported by Baer et al ( 2011 ) after a significant windstorm in the state of Washington in December 2006. A similar pattern was observed after a Colorado snowstorm in 2006, when 264 people, presented with CO poisoning symptoms (Musciatello et al 2006). Similarly, Schnall et al ( 2017 ) noted 566 cases of carbon monoxide poisoning post-Superstorm Sandy. Anderson and Bell ( 2012 ) also found that deaths from CO poisoning were accidental and more likely to occur in older age groups. Hospitals and emergency departments should expect an increase in ED visits because of incidents that occur after the hazard (Greenwald et al 2004 , Muscatiello et al 2010 , Johnson-Arbor et al 2014 , Schnall et al 2017 ).

3.2.1.2. Mental health impacts

Another concern related to health was the impacts on mental health during power outages. The longer duration that services, like electricity, were lost, the more likely signs of anxiety, depression, stress, and, in some cases, Post Traumatic Stress Disorder were to develop (Gros et al 2012 , Paradis 2012 , Apenteng et al 2018 , Moreno and Shaw 2019 ). However, if the outage lasted a short time, significantly less severe psychological symptoms were observed, primarily due to preparedness factors before the outage occurred (Gros et al 2012 ). ED visits for mental health reasons also increased during power outages (Lin et al 2016 , Rubin and Rogers 2019 ).

Other potential physical injuries may occur during a power outage from mental health impacts. During power outages, some people may resort to abusing substances to cope with the unusual times, like alcohol and drugs, adding to the danger of power outages (Jani et al 2006 , Lemieux 2014 , Lin et al 2016 ). Jani et al ( 2006 ) noted that of the 32 deaths examined from Hurricane Isabel, alcohol appeared to be involved in eight deaths and marijuana in one. All deaths occurred while completing tasks that require coordination and good judgment, for instance, driving in dangerous weather conditions (Jani et al 2006 ). Communication and messaging about the dangers of using these substances during and after extreme weather events are critical to limit the number of indirect deaths (Jani et al 2006 ).

3.2.1.3. Food-related impacts

Food-related illnesses also increase during and after power outages due to the consumption of spoiled food. Marx et al ( 2006 ) noticed an increase in ED visits in New York City after the 2003 Northeast blackout for symptoms of diarrheal illness. The authors could not establish a relationship between power outage and consuming spoiled food, as additional samples and data would be needed to further support their findings. However, the authors stated that spoiled food after the blackout may have caused an increase in ED visits (Marx et al 2006 ). Kosa et al ( 2011 ) highlighted through their study that many Americans are not prepared enough for a prolonged outage. Of those that experienced a power outage, only 37% discarded food that thawed in the freezer, and 31% discarded refrigerated perishable food that remained in the refrigerator for at least 4 h without power (Kosa et al 2011 ). From the sample, 33% of the sample knew to discard perishable foods, like meat, eggs, and dairy, after 4 h without power (Kosa et al 2011 ).

3.2.1.4. Medical devices

In addition to those that require hospitalization or care at a medical facility, people that require at-home care or are dependent on medical equipment outside of a medical facility, are vulnerable during power outages. Those that are dependent on medical devices, other than home oxygen therapy (HOT) equipment, are also more likely to call for emergency services during an outage (Rand et al 2005 ). During the 1977 New York City blackout, over 70 000 emergency calls were received in the 48 h blackout, as opposed to an average of 18 500 calls in 48 h under normal conditions (Imperato 2016 ). Those that require regular medical treatments (e.g. dialysis and other specialized medical practices) are vulnerable during power outages because of the possibility of missing treatments and not having a facility with reliable electricity to receive that treatment (Abir et al 2013 ). Device failure, from HOTs and ventilators, also led to an increase in ED visits, which requires significant ED and hospital resources (Greenwald et al 2004 ). The findings here indicate that patients who require HOT treatments need assistance before the storm so they can prepare for the post-event period without power (Esmalian et al 2019 ). Thus, planning for large-scale events, and more specifically planning where those who rely on electronic medical equipment need to be transported to receive the proper treatment, is a vital component of power outage preparedness, response, and recovery (Miles et al 2014 , Miles and Jagielo 2014 ).

3.2.2. Populations of concern

A common theme within the literature was the recognition that certain populations are more at risk for negative outcomes during a power outage. We found 29 studies that identified one or more populations of concern. Populations of concern identified through this research included children, non-English speakers, racial/ethnic minorities, older adults, and those that live in rural areas. While we identify these groups as populations of concern, we recognized most articles view this phrase in a vulnerability context. In using language that aligns with vulnerability, the definitions of what make a vulnerable population can vary. In this review, we attempted to synthesize the commonly identified populations of concern in the literature.

3.2.2.1. Children

Children, specifically under the age of 17, are a population of concern during power outages because of the greater risk of exposure to Carbon Monoxide (CO) poisoning because of improper generator use (Schnall et al 2017 ). This group was less aware of the dangers associated with power outages after Superstorm Sandy (Schnall et al 2017 ). Fife et al ( 2009 ) also found the number of children affected by CO poisoning was higher than other populations because they relied on technology for entertainment. This activity becomes a danger because children will use their devices near an operating generator while they are charging, leading to a greater risk of CO poisoning because of their proximity to the generator (Fife et al 2009 ).

3.2.2.2. English as a second language speakers

Those who do not speak English as their first language may not understand safety messaging provided only in English. Safety messaging emerged as a sub-theme in several studies that examined the intersection of language and power outage communication and messaging. The three studies that investigated the role of language consistently found that individuals with limited English proficiency were at higher risk of improper generator use or could not access or understand relevant safety information (Wrenn and Conners 1997 , Burger et al 2013 , Schnall et al 2017 ). Information that is available in multiple languages will assist this population most during power outages.

3.2.2.3. Racial and ethnic minorities

Racial and ethnic minority populations, more specifically African Americans, were reported to be at greater risk of adverse effects during power outages. Muhlin et al ( 1981 ) indicated that areas with greater minority populations were at greater risk to experience increased crime during a power outage. Lin et al ( 2016 ) also noted that those of low socioeconomic status experienced greater mental health problems, for example, anxiety, mood disorders, and substance abuse, because of a power outage. These impacts were present after Hurricane Sandy and highlighted the Bronx area, where roughly 44% of the population is Black according to a 2019 U.S. Census estimate, as a significant place of concern in the aftermath of Hurricane Sandy (Lin et al 2016 ).

3.2.2.4. Older adults

Older populations may also be at greater risk during power outages, as they are more likely to be dependent on medical equipment for chronic illness and increased mental health impacts (Anderson and Bell 2012 , Paradis 2012 , Lin et al 2016 ). Like those of lower socioeconomic status, Lin et al ( 2016 ) also found that older adult populations experience greater psychological symptoms during a power outage, such as increased stress, anxiety, depression, and the overall need for greater support—and should be prioritized. Similar findings were noted by Eachempati et al ( 2004 ), Gotanda et al ( 2015 ), and Rubin and Rogers ( 2019 ). However, Chakalian et al ( 2019 ) found the opposite after Hurricane Irma, noting that households with individuals over the age of 64 were less likely to experience stress or discomfort because of a hurricane or a blackout. This group was more self-reliant in mitigating impacts on their overall well-being and was more independent during these times than initially hypothesized (Chakalian et al 2019 ).

3.2.2.5. Rural populations

Rural populations are more likely to experience longer outages than those living in urbanized areas (Call 2010 , Gros et al 2012 ). In urban settings, the concentration of power lines that are considered high priority is centralized and located within proximity, leading to faster response and restoration times compared to surrounding rural areas (Call 2010 , Gros et al 2012 , Román et al 2019 ). Thus, providing rural areas with greater assistance after a significant event or during a prolonged power outage is necessary as electrical infrastructure in these areas is not as clustered as urbanized areas (Román et al 2019 ). However, due to previous experiences, this group may also be more prepared for longer outages, and better anticipate longer restoration times for future events (Román et al 2019 ).

3.2.2.6. Healthcare workers

Healthcare system workers are more likely to be overstressed and overworked during a power outage. The blackout that occurred in 2003 across the northeastern United States demonstrated that Specialists-in-Poison Information, workers in the Poison Control Center, were greatly overworked and had trouble finding time to rest during and after the blackout (Klein et al 2007 ). Workers experienced a significant increase in call volume both during the blackout and after power was restored (Eachempati et al 2004 , Freese et al 2006 , Klein et al 2007 , Paradis 2012 ). Freese et al ( 2006 ) found a statistically significant increase in the number of emergency calls made compared to a normal 24 h period. The increased call volume has the potential to impact healthcare workers mentally as they respond to a larger than normal number of emergency calls. This population needs attention to help avoid burnout and fatigue both during them outage and after power is restored.

3.2.2.7. Other populations

Lin et al ( 2011 ) indicated those of higher socioeconomic status should also be considered if a power outage occurred during the summer season as they are more likely to experience heat-related symptoms. Lin et al argued this group may have less experience dealing with uncertainty, for instance, a power outage, and less knowledge about how to keep cool in their homes during the summer months without air conditioning. This population can also afford healthcare and therefore receive treatment. Those of higher income are more likely to own resources that are necessary to stay cool in warmer temperatures, like air-conditioning. However, when these resources become unavailable during a power outage, those of higher income could have a lower capacity in dealing with warmer temperatures, both indoor and outdoor, and may be less aware of cooling strategies.

In the event of a power outage, the list of populations identified in this review serves as a starting point for practitioners to assess preparedness. Those that rely on medical equipment or suffer from chronic conditions are dependent on hospitals having reliable backup generators and running generators until power is restored. Should supplies run low, medical providers must be able to connect their customers with additional resources that can provide services until power is restored (Arya et al 2016 ). Therefore, both those that need medical equipment and those that provide medical services and care, including pharmacies, must be prepared for a prolonged power outage.

3.2.3. Criminal activity

A third theme that we identified in the literature centered on whether criminal activity increased because of power outages. While this theme was less of a focus than health impacts and populations of concern, we did find six articles that discussed the issue. Interestingly, while the literature discusses that criminal activity is theorized to occur post-hazard, this impact may be overstated; no articles in our review demonstrated that criminal activity increased post-natural hazard. When power outages occur independently of a hazard, crime and various criminal acts were more likely to occur due to an increase in motivation to commit crimes (Lemieux 2014 , Matthewman and Byrd 2014 ). Power outages and blackouts provide an opportunity for fraud, theft, and exploitation (Matthewman and Byrd 2014 ). Businesses located in poorer areas were more likely to be looted than businesses located in areas with greater economic prosperity (Sugarman 1978 , Wohlenberg 1982 ). Wohlenberg ( 1982 ) found that business owners in poorer areas that were harder hit by anti-social acts during a power outage intentionally burned their businesses. Other crimes not planned for may increase, such as generator theft and breaking into properties with an alternate power supply (Riddex and Dellgar 2001 ). If a blackout disrupts public services, authorities must expect pro- and anti-social activities to occur (Wohlenberg 1982 ).

However, this finding from Wohlenberg is contested both in findings from the literature for this review and in the disaster literature. Freese et al ( 2006 ) found that the crime rate did not change in comparison with the same dates in the previous year. The findings from Freese et al ( 2006 ) align with findings from the disaster literature, which indicates that an increase in criminal activity rarely occurs, despite heavy media attention directed towards isolated incidents (Quarantelli 2007 , Call 2010 , Lemieux 2014 ). But as Moreno and Shaw ( 2019 ) indicate, when looting did occur, instances of pro-social and anti-social looting occurred. People looted supermarkets for food and water (pro-social looting) and department stores for non-essential items like televisions and jewelry (anti-social looting). Looting affects perceptions of safety and trust within communities and can impact restoration times due to concerns over worker safety (Moreno and Shaw 2019 ).

Despite the potential for crime to occur, crimes can be mitigated with financial support and from local officials (Lemieux 2014 ). Financial assistance and food can be provided to reduce the crime rate during a power outage, but this solution is only temporary as the crime rate would increase once the initial relief has expired but power has not been restored (Rubin and Rogers 2019 ). This increase in crime could occur because of people requiring further assistance when additional assistance cannot be provided, which could lead to distress and unhappiness for persons needing resources.

3.3. Gaps within the literature

This review identifies a number of critical knowledge gaps in our understanding of power outage impacts. First and foremost, more research needs to consider the social impacts of power outages, which may increase in the future. Future research should put more effort into understanding how people are affected by more frequent power outages of shorter duration compared to longer and less frequently occurring power outages. While shorter outages may seem like only a nuisance to some, others may see more frequent outages as a significant concern, especially if they rely on a breathing machine or struggle to consistently afford essentials. For those that rely on dialysis treatments, for example, losing power while receiving treatments can be deadly if patients are not immediately taken off the machine. Knowing what impacts are anticipated with outages at certain lengths of time can help local organizations respond more effectively by providing sufficient resources that can aid those affected, especially those of lower income, that can last until power is restored.

The financial impacts of power outages have been under-investigated and would serve those of lower socioeconomic status, as they tend to struggle to afford essentials and may be disproportionately impacted by the loss of food or inability to work. While there have been studies that examined willingness-to-pay and how much people would be willing to pay to have consistent power to their residence, there have not been many that examined how people are financially affected by prolonged power outages (Carlsson and Martinsson 2008 , Abdullah and Mariel 2010 ). By examining how people are impacted financially can also help identify potential groups that may have difficulty recovering in the aftermath of a prolonged power outage, and greater assistance can be directed towards these areas to reduce the financial burden a prolonged power outage may cause, especially to those of lower income.

Considering these impacts from an environmental justice perspective can further highlight inequalities that exist within hazards and disasters. Previous research has indicated that there could be a relationship between demographic variables, like race and ethnicity, and power outage impacts highlighted from this review. While the findings were not statistically significant, further investigation is needed with stronger statistical samples to determine if power outage impacts align with previous research on the inequities that emerge from hazard- and disaster-related impacts.

The published research has focused more on how power outages are seen as an impact, rather than a separate hazard that occurs post-disaster. During the aftermath of a disaster, news and media coverage typically talk about people's experiences and how they are recovering from the event. There is not much discussion of power outages as a technological hazard and the societal consequences that may emerge from these events. Further research on this topic will be needed as the climate continues to evolve and will create weather scenarios that infrastructure was not designed for, whether it be extreme cold or heat. As these events become more frequent, and therefore placing infrastructure in a position to experience these scenarios more frequently, more people will be impacted by power outages, regardless of how the outage was initiated. Events like the Texas blackout the occurred in February 2021 would be of interest to study as Texans experienced anomalously cold temperatures and rolling outages over multiple days and before the recent infrastructure bill was signed into law.

Lastly, research should address how power outage impacts vary by season, particularly how summer and winter outages may present different hazards and require different responses. How someone prepares for a power outage in the winter will look differently than one that would occur in the summer; different resources would be required, but populations of concern would likely be similar.

4. Conclusion

In this review, we identified 50 articles that explored the social impacts of power outages. We identified many more articles focused on the technical impacts of power outages on electrical infrastructure. This emphasis on the technical impacts points to a need for more examination of these social impacts as the likelihood of outages increases. Some populations were disproportionately affected. Many populations of concern were identified including children, older adults, racial and ethnic minorities and those that live in rural areas. The greatest health concern that emerged during power outages was CO poisoning because of unsafe generator use during power outages. Hospitals should expect an increase in ED visits as more people will present with CO poisoning-related symptoms or require an operating medical device since patients' devices cannot work without electricity. Criminal acts increase during power outages, but crime rates can be reduced temporarily during prolonged power outages by providing aid and consistent updates on where to receive assistance and when power is expected to be restored. Looting most likely occurs in areas with lower socio-economic advantage; authorities should expect pro-social and anti-social resource appropriation during prolonged outages to occur as people see power outages as an opportunity to commit criminal acts (Barsky et al 2006). As power outages are expected to occur more frequently, understanding the differential effects across populations is critical to mitigating their impacts.

Future work can expand on this review by addressing the gaps identified in the literature. Studies of short duration but high frequency outages were not observed in this review but are increasingly salient with more frequent disturbances in grid reliability. More frequent outages may leave those that rely on medical devices more anxious because of uncertainty about when next power outage will occur. Increased power outages may lead to an increased likelihood of more food being spoiled and thrown away, which can represent a significant financial burden to lower-income households. Exploring power outages' effects may vary based on seasonality and temperature can provide context into how extreme cold and heat can influence household experiences and the different adaptation strategies deployed to reduce the potential impacts. Future work should also investigate power outage impacts from an environmental justice perspective to understand if power outage impacts align with other research that has highlighted racial disparities that occur with disasters.

This review highlights to the need to address the growing impact of a changing climate on the United States' already-deteriorating electrical infrastructure. Because of the increasing trend of reported electrical grid disturbances, research on the social impacts of power outages is vital in the context of a changing climate (Andresen 2020 ). While there has been an effort by the Biden Administration to address the deteriorating infrastructure, the ASCE ( 2021 ) Report Card has indicated that more money in addition to what has already been allocated by the recently signed legislation is needed to restore infrastructure to acceptable conditions. The effects of the increased investment in infrastructure will not be clear for some time. In the short term, the current infrastructure systems will remain fragile and weather events that bring anomalous weather conditions will stress electrical infrastructure systems that will cause an increase in power outages to occur and an increase in the number of people who are impacted.

Data availability statement

All data that support the findings of this study are included within the article (and any supplementary files).

Supplementary data (0.1 MB PDF)

Power Outages, Extreme Events and Health: A Systematic Review of the Literature from 2011-2012

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Prepare Yourself for a Power Outage

This summer it’s possible your household will lose power. Above average temperatures are causing extreme heat and drought, which has elevated the risk of power outages throughout the country.

A power outage is when the electrical power goes out unexpectedly, potentially, lasting a few hours.  For that reason, it is important to know how to protect yourself during an extended power outage.

Here are four ways to prepare yourself for a power outage:

Find Alternate Power Source. Plan for batteries and alternative power sources to meet your needs when the power goes out, such as a portable charger or power bank. Have flashlights for every household member. Determine whether your home phone will work in a power outage and how long battery backup will last. Remember, never use a generator indoors.

Appliances. Disconnect appliances and electronics to avoid damage from electrical surges. Install carbon monoxide detectors with battery backup in central locations on every level of your home to avoid carbon monoxide poisoning.

Food Storage. Keep freezers and refrigerators closed. A refrigerator will keep food cold for four hours. A full freezer will keep the temperature for about 48 hours. If you are in doubt, monitor temperatures with a thermometer and throw out food if the temperature is 40 degrees or higher. Maintain a few days’ supply of nonperishable food and water.

Know Your Medical Needs. If you rely on electricity for any medical needs, make a power outage plan for medical devices or refrigerated medicines. Find out how long medication can be stored at higher temperatures and get specific guidance for any medications that are critical for life.

If you are without power during extreme temperatures, consider going to a community location to keep safe.

For more information on how to be prepared for a power outage, visit Ready.gov .

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Review on causes of power outages and their occurrence: mitigation strategies.

1. Introduction

1.1. motivations and overview, 1.2. topology of grid utilities, 1.3. review structure and contributions.

• To the best of our knowledge, this work is the first review to widely cover the causes of power outages that some countries suffer from, especially the rolling blackouts imposed by national grid companies like in Iraq. This includes power transmission and distribution outages due to technical reasons, natural weather conditions, power plant faults, accidents, over-demand, and bypassing/hacking the power national grid.
• Unlike existing reviews [ 24 , 25 , 26 , 27 ] that concentrated on demand-side energy management, we specifically focus on power outage causes for developing countries like Iraq rather than all management strategies.
• This paper covers the most advanced and recent progress to overcome the planned power outages of the power grid. Therefore, it presents readers with state-of-the-art strategies.

2. Causes of Power Outages

• Blackout: A blackout happens when the entire system fails. The worst power outage so far is this one. Power restoration can be challenging, particularly when power stations are damaged and the grid is tripped. These disruptions can extend for several hours, days, or even weeks.
• Brownout: Unlike a blackout, which results in a complete loss of electricity, a brownout only results in a temporary reduction in power. This kind of interruption can prevent the grid from becoming overloaded and entering a complete blackout. Rolling brownouts occur when the electricity grid loses power in discrete areas.
• Permanent fault: it does not last forever. Faults include imbalanced voltage or current as well as flow disruptions. The electricity is restored once the fault has been fixed. Because it will not correct itself or reset without intervention, the problem is referred to as permanent.

3. Consequences of Power Outages

3.1. analysis of distribution power losses.

• In a distribution network, fixed technical losses account for 1/4 to 1/3 of all technical losses. This can happen whenever the transformer is powered and typically manifests as noise and heat. The fixed losses are more affected by leakage current losses, dielectric losses, corona losses, etc., than by the amount of load current flowing.
• Between two-thirds and three-quarters of the distribution system, technical losses are made up of technical variable losses that are proportional to the load current square. Joule heating losses, contact resistance, and line impedance all have an impact on the variable losses.

3.2. Reliability Indices

3.2.1. average energy not supplied (aens), 3.2.2. energy not supplied (ens), 3.2.3. average service availability index (asai), 3.2.4. customer average interruption duration index (caidi), 3.2.5. system average interruption frequency index (saifi), 3.2.6. system average interruption duration index (saidi), 3.3. producing systems reliability indices, 3.3.1. lolp, 3.3.2. eue and lolh, 3.3.3. lole, 3.3.4. lolev, 3.3.5. loep, 3.3.6. epns, 3.4. economic losses due to non-delivery of power, 3.5. financially losing from power blackouts, 3.6. power blackouts in firms in a typical month, 4. power outage mitigation strategies, 4.1. demand side em.

• Demand response (DR), which gives end users the ability to vary their load consumption patterns in reaction to an increase or decrease in the price of power over time, lowering the system’s overall peak.
• Energy efficiency places a strong emphasis on encouraging customers to use efficient products as a way to cut demand [ 129 , 135 , 136 ].

4.2. Generation-Side EM

• Distribution and transmission of electrical power, including substations, lines, and on-site generating, are examples of generation-side EM. Transfer of solid, liquid, and gaseous fuels.
• Energy conversion and power generation, including cogeneration and operational upgrades to existing plants.
• Energy resource supply and use, including the use of renewable energy sources, fuel substitution, and clean coal technology.
• Since the over-demand of electricity forces the national utility company to apply rolling/planned power outages, generation-side-based EM with an appropriate strategy is a method that can help improve management strategy performance. This technique is recommended by this work for cases like Iraq.
• Minimize environmental impact;
• Supply the highest value to its clients by reducing energy charges;
• Make sure of consistent availability of energy at the minimum financial cost eventually growing its profits;
• Satisfy rising electricity demand without needless significant capital expenditures for additional producing capacity.

5. Power Outages in Iraq as a Case Study

• Daily Average Output: 4470 MWh;
• Daily Electricity Demand: 6400 MWh;
• 6900–7800 MWh, or 36–45% of the summer peak demand, cannot currently be satisfied.

5.1. Formulation of Iraq’s Electricity Problem

5.2. limitations of the reviewed studies, 5.3. statistics for the reviewed publications, 5.4. classification and a recommended solution, 6. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Khoucha, F.; Benbouzid, M.; Amirat, Y.; Kheloui, A. Integrated energy management of a plug-in electric vehicle in residential distribution systems with renewables. In Proceedings of the 2015 IEEE 24th International Symposium on Industrial Electronics (ISIE), Buzios, Brazil, 3–5 June 2015; pp. 717–722. [ Google Scholar ] [ CrossRef ]
• Wang, S.; Xue, X.; Yan, C. Building power demand response methods toward smart grid. HVAC&R Res. 2014 , 20 , 665–687. [ Google Scholar ] [ CrossRef ]
• Conchado, A.; Linares, P. The economic impact of demand-response programs on power systems. A survey of the state of the art. In Handbook of Networks in Power Systems ; Springer: Berlin/Heidelberg, Germany, 2011; pp. 281–301. [ Google Scholar ] [ CrossRef ]
• Ożadowicz, A. A new concept of active demand side management for energy efficient prosumer microgrids with smart building technologies. Energies 2017 , 10 , 1771. [ Google Scholar ] [ CrossRef ]
• Chen, X.; Li, J.; Yang, A.; Zhang, Q. Artificial neural network-aided energy management scheme for unlocking demand response. In Proceedings of the 2020 Chinese Control and Decision Conference (CCDC), Hefei, China, 22–24 August 2020; pp. 1901–1905. [ Google Scholar ] [ CrossRef ]
• Inoyatov, B.D.; Raseel, A.; Tulsky, V.N.; Dzhuraev, S.D. Power quality monitoring as a tool for phase conductors diagnostics. In Proceedings of the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), Saint Petersburg and Moscow, Russia, 28–31 January 2019; pp. 973–976. [ Google Scholar ] [ CrossRef ]
• Das, L.N.; Gupta, S. RETRACTED ARTICLE: Electrical power system transmission quality and power supplier micro grid control functional reliability. Int. J. Syst. Assur. Eng. Manag. 2020 , 11 , 325–328. [ Google Scholar ] [ CrossRef ]
• Park, E.; Kim, B.; Park, S.; Kim, D. Analysis of the effects of the home energy management system from an open innovation perspective. J. Open Innov. Technol. Mark. Complex. 2018 , 4 , 31. [ Google Scholar ] [ CrossRef ]
• Zunnurain, I.; Maruf, N.I.; Rahman, M.; Shafiullah, G. Implementation of advanced demand side management for microgrid incorporating demand response and home energy management system. Infrastructures 2018 , 3 , 50. [ Google Scholar ] [ CrossRef ]
• Chen, Z.; Wu, L.; Fu, Y. Real-time price-based demand response management for residential appliances via stochastic optimization and robust optimization. IEEE Trans. Smart Grid 2012 , 3 , 1822–1831. [ Google Scholar ] [ CrossRef ]
• Yu, J.; Dou, C.; Li, X. MAS-based energy management strategies for a hybrid energy generation system. IEEE Trans. Ind. Electron. 2016 , 63 , 3756–3764. [ Google Scholar ] [ CrossRef ]
• Yang, R.; Yuan, Y.; Ying, R.; Shen, B.; Long, T. A novel energy management strategy for a ship’s hybrid solar energy generation system using a particle swarm optimization algorithm. Energies 2020 , 13 , 1380. [ Google Scholar ] [ CrossRef ]
• Teng, T.; Zhang, X.; Dong, H.; Xue, Q. A comprehensive review of energy management optimization strategies for fuel cell passenger vehicle. Int. J. Hydrogen Energy 2020 , 45 , 20293–20303. [ Google Scholar ] [ CrossRef ]
• Arcos-Aviles, D.; Pascual, J.; Guinjoan, F.; Marroyo, L.; Sanchis, P.; Marietta, M.P. Low complexity energy management strategy for grid profile smoothing of a residential grid-connected microgrid using generation and demand forecasting. Appl. Energy 2017 , 205 , 69–84. [ Google Scholar ] [ CrossRef ]
• Patrone, M.; Feroldi, D. Passivity-based control design for a grid-connected hybrid generation system integrated with the energy management strategy. J. Process. Control. 2019 , 74 , 99–109. [ Google Scholar ] [ CrossRef ]
• Angeloudis, A.; Kramer, S.C.; Avdis, A.; Piggott, M.D. Optimising tidal range power plant operation. Appl. Energy 2018 , 212 , 680–690. [ Google Scholar ] [ CrossRef ]
• Bansal, A.K. Sizing and forecasting techniques in photovoltaic-wind based hybrid renewable energy system: A review. J. Clean. Prod. 2022 , 369 , 133376. [ Google Scholar ] [ CrossRef ]
• Jena, N.K.; Sahoo, S.; Sahu, B.K.; Nayak, J.R.; Mohanty, K.B. Fuzzy adaptive selfish herd optimization based optimal sliding mode controller for frequency stability enhancement of a microgrid. Eng. Sci. Technol. Int. J. 2021 , 33 , 101071. [ Google Scholar ] [ CrossRef ]
• Magdy, G.; Shabib, G.; Elbaset, A.A.; Mitani, Y. Optimized coordinated control of LFC and SMES to enhance frequency stability of a real multi-source power system considering high renewable energy penetration. Prot. Control. Mod. Power Syst. 2018 , 3 , 39. [ Google Scholar ] [ CrossRef ]
• Sabry, A.H.; Hasan, W.Z.W.; Zainal, M.; Amran, M.; Shafie, S.B. Alternative solar-battery charge controller to improve system efficiency. Appl. Mech. Mater. 2015 , 785 , 156–161. [ Google Scholar ]
• Di Silvestre, M.L.; Gallo, P.; Guerrero, J.M.; Musca, R.; Sanseverino, E.R.; Sciumè, G.; Vasquez, J.C.; Zizzo, G. Blockchain for power systems: Current trends and future applications. Renew. Sustain. Energy Rev. 2020 , 119 , 109585. [ Google Scholar ] [ CrossRef ]
• Sabry, A.H.; Ker, P.J. DC Environment for a refrigerator with variable speed compressor; Power consumption profile and performance comparison. IEEE Access 2020 , 8 , 147973–147982. [ Google Scholar ] [ CrossRef ]
• Xu, Y.; Tan, Z.; Guo, L.; Zhao, Y.; Wu, J. An optimal dispatching method with multi-microgrid for flexible medium voltage DC distribution center. Power Syst. Prot. Control. 2019 , 47 , 148–158. [ Google Scholar ] [ CrossRef ]
• Groppi, D.; Pfeifer, A.; Garcia, D.A.; Krajačić, G.; Duić, N. A review on energy storage and demand side management solutions in smart energy islands. Renew. Sustain. Energy Rev. 2021 , 135 , 110183. [ Google Scholar ] [ CrossRef ]
• Kaspar, K.; Ouf, M.; Eicker, U. A critical review of control schemes for demand-side energy management of building clusters. Energy Build. 2022 , 257 , 111731. [ Google Scholar ] [ CrossRef ]
• Mariano-Hernández, D.; Hernández-Callejo, L.; Zorita-Lamadrid, A.; Duque-Pérez, O.; García, F.S. A review of strategies for building energy management system: Model predictive control, demand side management, optimization, and fault detect & diagnosis. J. Build. Eng. 2021 , 33 , 101692. [ Google Scholar ] [ CrossRef ]
• Uddin, M.; Romlie, M.F.; Abdullah, M.F.; Halim, S.A.; Kwang, T.C. A review on peak load shaving strategies. Renew. Sustain. Energy Rev. 2018 , 82 , 3323–3332. [ Google Scholar ] [ CrossRef ]
• Melodi, A.O.; Oyeleye, O.M. Modeling of lightning strike events, and it’s correlational with power outages in south-west coast, nigeria. Int. J. Electr. Comput. Eng. (IJECE) 2017 , 7 , 3262–3270. [ Google Scholar ] [ CrossRef ]
• Rawi, I.M.; Kadir, M.Z.A.A.; Izadi, M. Seasonal variation of transmission line outages in peninsular Malaysia. Pertanika J. Sci. Technol. 2017 , 25 , 213–220. [ Google Scholar ]
• Sindiramutty, S.R.; Eng, C.; Ping, S. Priority based energy distribution for off-grid rural electrification. Int. J. Adv. Comput. Sci. Appl. 2020 , 11 , 110354. [ Google Scholar ] [ CrossRef ]
• Shield, S.A.; Quiring, S.M.; Pino, J.V.; Buckstaff, K. Major impacts of weather events on the electrical power delivery system in the United States. Energy 2021 , 218 , 119434. [ Google Scholar ] [ CrossRef ]
• Campbell, R.J. Weather-related power outages and electric system resiliency specialist in energy policy weather-related power outages and electric system resiliency. In CRS Report for Congress ; Library of Congress, Congressional Research Service: Washington, DC, USA, 2012. [ Google Scholar ]
• Campbell, R.J. Weather-related power outages and electric system resiliency. In The Transformation of Electrical Power: Key Issues ; Library of Congress, Congressional Research Service: Washington, DC, USA, 2013. [ Google Scholar ]
• Xu, J.; Yao, R.; Qiu, F. Mitigating cascading outages in severe weather using simulation-based optimization. IEEE Trans. Power Syst. 2021 , 36 , 204–213. [ Google Scholar ] [ CrossRef ]
• Wang, Z.; Hong, T.; Li, H. Informing the planning of rotating power outages in heat waves through data analytics of connected smart thermostats for residential buildings. Environ. Res. Lett. 2021 , 16 , 074003. [ Google Scholar ] [ CrossRef ]
• Yum, S.-G.; Son, K.; Son, S.; Kim, J.-M. Identifying risk indicators for natural hazard-related power outages as a component of risk assessment: An analysis using power outage data from hurricane irma. Sustainability 2020 , 12 , 7702. [ Google Scholar ] [ CrossRef ]
• Chen, F.; Li, F.; Wei, Z.; Sun, G.; Li, J. Reliability models of wind farms considering wind speed correlation and WTG outage. Electr. Power Syst. Res. 2015 , 119 , 385–392. [ Google Scholar ] [ CrossRef ]
• Portante, E.C.; Folga, S.F.; Kavicky, J.A.; Malone, L.T. Simulation of the 8 September 2011, San Diego blackout. In Proceedings of the Winter Simulation Conference 2014, Savannah, GA, USA, 7–10 December 2014; pp. 1527–1538. [ Google Scholar ] [ CrossRef ]
• Fan, X.; Agrawal, U.; Davis, S.; O’Brien, J.; Etingov, P.; Nguyen, T.; Makarov, Y.; Samaan, N. Bulk electric system protection model demonstration with 2011 southwest blackout in DCAT. In Proceedings of the 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Canada, 2–6 August 2020; pp. 1–5. [ Google Scholar ] [ CrossRef ]
• Lin, W.; Tang, Y.; Sun, H.; Guo, Q.; Zhao, H.; Zeng, B. Blackout in Brazil power grid on February 4, 2011 and inspirations for stable operation of power grid. Autom. Electr. Power Syst. 2011 , 35 , 1–9. [ Google Scholar ]
• Liu, Y.; Shu, Z.; Cheng, X.; Zhang, S. Analyzing the principle of protection through the blackout in Brazil power grid on February 4. Autom. Electr. Power Syst. 2011 , 35 . Available online: https://xueshu.baidu.com/usercenter/paper/show?paperid=fa2f9925fa67c63ab96965cb56b74344&site=xueshu_se (accessed on 8 June 2023).
• Lai, L.L.; Ramasubramanian, D.; Zhang, H.T.; Xu, F.Y.; Mishra, S.; Lai, C.S. Lessons Learned from July 2012 Indian Blackout. In Proceedings of the 9th IET International Conference on Advances in Power System Control, Operation and Management (APSCOM 2012, Hong Kong, China, 18–21 November 2012. [ Google Scholar ] [ CrossRef ]
• Tang, Y.; Bu, G.; Yi, J. Analysis and lessons of the blackout in Indian power grid on July 30 and 31. Proc. Chin. Soc. Electr. Eng. 2012 , 32 , 167–174. [ Google Scholar ]
• Hines, P.D.H.; Dobson, I.; Rezaei, P. Cascading power outages propagate locally in an influence graph that is not the actual grid topology. IEEE Trans. Power Syst. 2017 , 32 , 958–967. [ Google Scholar ] [ CrossRef ]
• Kaiser, F.; Latora, V.; Witthaut, D. Network isolators inhibit failure spreading in complex networks. Nat. Commun. 2021 , 12 , 3143. [ Google Scholar ] [ CrossRef ]
• Adnan, M.; Khan, M.G.; Amin, A.A.; Fazal, M.R.; Tan, W.-S.; Ali, M. Cascading failures assessment in renewable integrated power grids under multiple faults contingencies. IEEE Access 2021 , 9 , 82272–82287. [ Google Scholar ] [ CrossRef ]
• Zhou, Z.; Shi, L. Risk assessment of power system cascading failure considering wind power uncertainty and system frequency modulation. Proc. Chin. Soc. Electr. Eng. 2021 , 22 , 1–12. [ Google Scholar ] [ CrossRef ]
• Bose, D.; Chanda, C.K.; Chakrabarti, A. Complex network theory based analysis of cascading failure of electrical power transmission network against intentional attacks and outages. In Proceedings of the Michael Faraday IET International Summit 2020 (MFIIS 2020), Online, 3–4 October 2020; pp. 255–260. [ Google Scholar ] [ CrossRef ]
• Kondrateva, O.; Myasnikova, E.; Loktionov, O. Analysis of the climatic factors influence on the overhead transmission lines reliability. Sci. J. Riga Tech. Univ. Environ. Clim. Technol. 2021 , 24 , 201–214. [ Google Scholar ] [ CrossRef ]
• Yang, S.; Zhou, W.; Zhu, S.; Wang, L.; Ye, L.; Xia, X.; Li, H. Failure probability estimation of overhead transmission lines considering the spatial and temporal variation in severe weather. J. Mod. Power Syst. Clean Energy 2019 , 7 , 131–138. [ Google Scholar ] [ CrossRef ]
• Guo, L.; Liang, C.; Zocca, A.; Low, S.H.; Wierman, A. Line failure localization of power networks part II: Cut set outages. IEEE Trans. Power Syst. 2021 , 36 , 4152–4160. [ Google Scholar ] [ CrossRef ]
• Moghavvemi, M.; Faruque, M. Power system security and voltage collapse: A line outage based indicator for prediction. Int. J. Electr. Power Energy Syst. 1999 , 21 , 455–461. [ Google Scholar ] [ CrossRef ]
• Ravindra, S.; Reddy, V.; Sivanagaraju, S. Power system security analysis under transmission line outage condition. IJIREEICE 2015 , 3 , 46–50. [ Google Scholar ] [ CrossRef ]
• Kutjuns, A.; Kovalenko, S.; Zemite, L.; Zbanovs, A. Analysis of faults impact on gas and electricity systems. In Proceedings of the 2018 19th International Scientific Conference on Electric Power Engineering (EPE), Brno, Czech Republic, 16–18 May 2018; pp. 1–5. [ Google Scholar ] [ CrossRef ]
• Hibti, M.; Vasseur, D. A declarative approach for risk outage management. In Proceedings of the 10th International Conference on Probabilistic Safety Assessment and Management 2010, PSAM 2010, Seattle, WA, USA, 7–11 June 2010. [ Google Scholar ]
• Kataoka, T.; Shitsukawa, M.; Tajimi, A. Improvement in coordinated restoration operation skills covering more than one area (Developing a power system operation training simulator that precisely reproduces electrical phenomena). In Proceedings of the 44th International Conference on Large High Voltage Electric Systems 2012, Paris, France, 25–30 August 2012. [ Google Scholar ]
• Zhang, Z.; Huang, S.; Liu, F.; Mei, S. Pattern analysis of topological attacks in cyber-physical power systems considering cascading outages. IEEE Access 2020 , 8 , 134257–134267. [ Google Scholar ] [ CrossRef ]
• Chung, H.-M.; Li, W.-T.; Yuen, C.; Chung, W.-H.; Zhang, Y.; Wen, C.-K. Local cyber-physical attack for masking line outage and topology attack in smart grid. IEEE Trans. Smart Grid 2019 , 10 , 4577–4588. [ Google Scholar ] [ CrossRef ]
• Sifat, M.H.; Choudhury, S.M.; Das, S.K.; Ahamed, H.; Muyeen, S.; Hasan, M.; Ali, F.; Tasneem, Z.; Islam, M.; Islam, R.; et al. Towards electric digital twin grid: Technology and framework review. Energy AI 2023 , 11 , 100213. [ Google Scholar ] [ CrossRef ]
• Obar, E.A.; Touati, A.; Adekanle, O.S.; Agajelu, B.; Moulebe, L.P.; Rabbah, N. Navigating the prevailing challenges of the nigerian power sector. WSEAS Trans. Power Syst. 2022 , 17 , 234–243. [ Google Scholar ] [ CrossRef ]
• McCreight, R. Grid collapse security, stability and vulnerability issues: Impactful issues affecting nuclear power plants, chemical plants and natural gas supply systems. J. Homel. Secur. Emerg. Manag. 2019 , 16 , 20180021. [ Google Scholar ] [ CrossRef ]
• Sullivan, J.E.; Kamensky, D. How cyber-attacks in Ukraine show the vulnerability of the U.S. power grid. Electr. J. 2017 , 30 , 30–35. [ Google Scholar ] [ CrossRef ]
• Brezhniev, E.; Ivanchenko, O. NPP-smart grid mutual safety and cyber security assurance. In Research Anthology on Smart Grid and Microgrid Development ; IGI Global: Hershey, PA, USA, 2022; pp. 1047–1077. [ Google Scholar ] [ CrossRef ]
• Tippachon, W.; Kwansawaitham, A.; Klairuang, N.; Rerkpreedapong, D.; Hokierti, J. Failure analysis of power distribution systems in Thailand. In Proceedings of the 2006 International Conference on Power System Technology, Chongqing, China, 22–26 October 2006; pp. 1–5. [ Google Scholar ] [ CrossRef ]
• Parshall, L.; Pillai, D.; Mohan, S.; Sanoh, A.; Modi, V. National electricity planning in settings with low pre-existing grid coverage: Development of a spatial model and case study of Kenya. Energy Policy 2009 , 37 , 2395–2410. [ Google Scholar ] [ CrossRef ]
• Zohrabian, A.; Sanders, K.T. The energy trade-offs of transitioning to a locally sourced water supply portfolio in the city of Los Angeles. Energies 2020 , 13 , 5589. [ Google Scholar ] [ CrossRef ]
• Masood, B.; Guobing, S.; Nebhen, J.; Rehman, A.U.; Iqbal, M.N.; Rasheed, I.; Bajaj, M.; Shafiq, M.; Hamam, H. Investigation and field measurements for demand side management control technique of smart air conditioners located at residential, commercial, and industrial sites. Energies 2022 , 15 , 2482. [ Google Scholar ] [ CrossRef ]
• Asogwa, B.E. Electronic government as a paradigm shift for efficient public services. Libr. Hi Tech 2013 , 31 , 141–159. [ Google Scholar ] [ CrossRef ]
• Abdullateef, A.; Sulaiman, A.; Issa, A.; Zakariyya, S. Design and implementation of a cloud-based load monitoring scheme for electricity theft detection on a conventional grid. Jordan J. Electr. Eng. 2022 , 8 , 322–338. [ Google Scholar ] [ CrossRef ]
• HaesAlhelou, H.; Hamedani-Golshan, M.E.; Njenda, T.C.; Siano, P. A survey on power system blackout and cascading events: Research motivations and challenges. Energies 2019 , 12 , 682. [ Google Scholar ] [ CrossRef ]
• Kumar, N.M.; Ghosh, A.; Chopra, S.S. Power resilience enhancement of a residential electricity user using photovoltaics and a battery energy storage system under uncertainty conditions. Energies 2020 , 13 , 4193. [ Google Scholar ] [ CrossRef ]
• Suhono, S.; Sarjiya, S.; Hadi, S.P. Electricity demand and supply planning analysis for sumatera interconnection system using integrated resources planning approach. J. Ilm. Tek. Elektro Komput. Dan Inform. 2019 , 5 , 16–25. [ Google Scholar ] [ CrossRef ]
• Chen, B.; Xiang, K.; Yang, L.; Su, Q.; Huang, D.; Huang, T. Theoretical line loss calculation of distribution network based on the integrated electricity and line loss management system. In Proceedings of the 2018 China International Conference on Electricity Distribution (CICED), Tianjin, China, 17–19 September 2018; pp. 2531–2535. [ Google Scholar ] [ CrossRef ]
• Feng, S.; Licheng, Y.; Zhitong, G.; Yanhong, C. Reactive power optimization compensation of line losses calculation in rural areas. In Proceedings of the 2018 Chinese Control and Decision Conference (CCDC), Shenyang, China, 9–11 June 2018; pp. 6458–6463. [ Google Scholar ] [ CrossRef ]
• Al-Mahroqi, Y.; Metwally, I.A.; Al-Hinai, A.; Al-Badi, A. Reduction of power losses in distribution systems. Int. J. Electr. Comput. Energetic Electron. Commun. Eng. 2012 , 6 , 315–322. [ Google Scholar ]
• Hamzaoğlu, A.; Erduman, A.; Alçı, M. Reduction of distribution system losses using solar energy cooperativity by home user. Ain Shams Eng. J. 2021 , 12 , 3737–3745. [ Google Scholar ] [ CrossRef ]
• Nguyen, T.T.; Dinh, B.H.; Pham, T.D.; Nguyen, T.T. Active power loss reduction for radial distribution systems by placing capacitors and PV systems with geography location constraints. Sustainability 2020 , 12 , 7806. [ Google Scholar ] [ CrossRef ]
• Yang, N.-C.; Zeng, Y.-L.; Chen, T.-H. Assessment of voltage imbalance improvement and power loss reduction in residential distribution systems in Taiwan. Mathematics 2021 , 9 , 3254. [ Google Scholar ] [ CrossRef ]
• Navani, P.J. Technical and non-technical losses in power system and its economic consequences in indian economy. Int. J. Electron. Comput. Sci. Eng. (IJESCE) 2009 , 1 , 757–761. [ Google Scholar ]
• Chauhan, A.; Rajvanshi, S. Non-technical losses in power system: A review. In Proceedings of the 2013 International Conference on Power, Energy and Control (ICPEC), Dindigul, India, 6–8 February 2013; pp. 558–561. [ Google Scholar ] [ CrossRef ]
• Komolafe, O.; Udofia, K. Review of electrical energy losses in Nigeria. Niger. J. Technol. 2020 , 39 , 246–254. [ Google Scholar ] [ CrossRef ]
• Ahmad, T. Non-technical loss analysis and prevention using smart meters. Renew. Sustain. Energy Rev. 2017 , 72 , 573–589. [ Google Scholar ] [ CrossRef ]
• Blazakis, K.V.; Kapetanakis, T.N.; Stavrakakis, G.S. Effective electricity theft detection in power distribution grids using an adaptive neuro fuzzy inference system. Energies 2020 , 13 , 3110. [ Google Scholar ] [ CrossRef ]
• Rodrigo, A.S.; Gunatillaka, M.D.P.R. An effective method of segregation of losses in distribution systems. Eng. J. Inst. Eng. Sri Lanka 2019 , 52 , 1–14. [ Google Scholar ] [ CrossRef ]
• Xiao, H.; Lin, C.; Kou, G.; Peng, R. Reliability modeling and configuration optimization of a photovoltaic based electric power generation system. Reliab. Eng. Syst. Saf. 2022 , 220 , 108285. [ Google Scholar ] [ CrossRef ]
• Yin, S.-A.; Lu, C.-N. Distribution feeder scheduling considering variable load profile and outage costs. IEEE Trans. Power Syst. 2009 , 24 , 652–660. [ Google Scholar ] [ CrossRef ]
• Singh, B.; Gyanish, B.J. Impact assessment of DG in distribution systems from minimization of total real power loss viewpoint by using optimal power flow algorithms. Energy Rep. 2018 , 4 , 407–417. [ Google Scholar ] [ CrossRef ]
• Rajendran, A.; Narayanan, K. Optimal multiple installation of DG and capacitor for energy loss reduction and loadability enhancement in the radial distribution network using the hybrid WIPSO–GSA algorithm. Int. J. Ambient. Energy 2020 , 41 , 129–141. [ Google Scholar ] [ CrossRef ]
• Mello, J.; Pereira, M.; da Silva, A.L. Evaluation of reliability worth in composite systems based on pseudo-sequential Monte Carlo simulation. IEEE Trans. Power Syst. 1994 , 9 , 1318–1326. [ Google Scholar ] [ CrossRef ]
• Srividhya, P.; Mounika, K.; Kirithikaa, S.; Narayanan, K.; Sharma, G.; Girish Ganesan, R.; Senjyu, T. Reliability improvement of radial distribution system by reconfiguration. Adv. Sci. Technol. Eng. Syst. J. 2020 , 5 , 472–480. [ Google Scholar ] [ CrossRef ]
• Subcommittee, D. IEEE guide for electric power distribution reliability indices. Distribution 2012 , 1997 , 1–43. [ Google Scholar ]
• Kim, S.-Y.; Kim, J.-O. Reliability evaluation of distribution network with DG considering the reliability of protective devices affected by SFCL. IEEE Trans. Appl. Supercond. 2011 , 21 , 3561–3569. [ Google Scholar ] [ CrossRef ]
• Rusin, A.; Wojaczek, A. Trends of changes in the power generation system structure and their impact on the system reliability. Energy 2015 , 92 , 128–134. [ Google Scholar ] [ CrossRef ]
• IEEE Std 1012-1998 ; IEEE Standard for Software Verification and Validation. IEEE Institute of Electrical and Electronics Engineers: NewYork, NY, USA, 1998.
• Kim, H.; Sioshansi, R.; Lannoye, E.; Ela, E. A stochastic-dynamic-optimization approach to estimating the capacity value of energy storage. IEEE Trans. Power Syst. 2022 , 37 , 1809–1819. [ Google Scholar ] [ CrossRef ]
• Menaem, A.A.; Valiev, R.; Oboskalov, V.; Hassan, T.S.; Rezk, H.; Ibrahim, M.N. An efficient framework for adequacy evaluation through extraction of rare load curtailment events in composite power systems. Mathematics 2020 , 8 , 2021. [ Google Scholar ] [ CrossRef ]
• Madhura, S. Energy management system for domestic applications. J. Electr. Eng. Autom. 2022 , 4 , 220–230. [ Google Scholar ] [ CrossRef ]
• Schröder, T.; Kuckshinrichs, W. Value of lost load: An efficient economic indicator for power supply security? A literature review. Front. Energy Res. 2015 , 3 , 55. [ Google Scholar ] [ CrossRef ]
• Majchrzak, D.; Michalski, K.; Reginia-Zacharski, J. Readiness of the polish crisis management system to respond to long-term, large-scale power shortages and failures (blackouts). Energies 2021 , 14 , 8286. [ Google Scholar ] [ CrossRef ]
• Thomas, D.; Fung, J. Measuring downstream supply chain losses due to power disturbances. Energy Econ. 2022 , 114 , 106314. [ Google Scholar ] [ CrossRef ]
• Pasha, H.A.; Saleem, W. The impact and cost of power load shedding to domestic consumers. Pak. Dev. Rev. 2013 , 52 , 355–373. [ Google Scholar ] [ CrossRef ]
• Ebrahimi, H.; Abapour, M.; Mohammadi-Ivatloo, B.; Golshannavaz, S. Security constrained optimal power flow in a power system based on energy storage system with high wind penetration. Sci. Iran. 2020 , 29 , 1475–1485. [ Google Scholar ] [ CrossRef ]
• Safdar, M.; Hussain, G.A.; Lehtonen, M. Costs of demand response from residential customers’ perspective. Energies 2019 , 12 , 1617. [ Google Scholar ] [ CrossRef ]
• Bateman, I.J.; Burgess, D.; Hutchinson, W.G.; Matthews, D.I. Learning design contingent valuation (LDCV): NOAA guidelines, preference learning and coherent arbitrariness. J. Environ. Econ. Manag. 2008 , 55 , 127–141. [ Google Scholar ] [ CrossRef ]
• Pasha, H.A.; Ghaus, A.; Malik, S. The economic cost of power outages in the industrial sector of Pakistan. Energy Econ. 1989 , 11 , 301–318. [ Google Scholar ] [ CrossRef ]
• Baloch, M.H.; Chauhdary, S.T.; Ishak, D.; Kaloi, G.S.; Nadeem, M.H.; Wattoo, W.A.; Younas, T.; Hamid, H.T. Hybrid energy sources status of Pakistan: An optimal technical proposal to solve the power crises issues. Energy Strat. Rev. 2019 , 24 , 132–153. [ Google Scholar ] [ CrossRef ]
• Li, L.; Ji, L.; Zhang, Y.; Sun, W.; An, X.; Tu, J.; He, J.; Zhou, Q.; Jiang, H. Preliminary analysis and lessons of blackout in pakistan power grid on January 9. Power Syst. Technol. 2022 , 46 , 655–661. [ Google Scholar ] [ CrossRef ]
• Al-Shetwi, A.Q.; Hannan, M.A.; Abdullah, M.A.; Rahman, M.S.A.; Ker, P.J.; Alkahtani, A.A.; Mahlia, T.M.I.; Muttaqi, K.M. Utilization of renewable energy for power sector in yemen: Current status and potential capabilities. IEEE Access 2021 , 9 , 79278–79292. [ Google Scholar ] [ CrossRef ]
• Al-Bashiri, M. Impacts of the War on the Telecommunications Sector in Yemen. Rethink. Yemen’s Econ. 2021. Available online: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Impacts+of+the+war+on+the+telecommunications+sector+in+yemen&btnG= (accessed on 8 June 2023).
• Timilsina, G.; Steinbuks, J. Economic costs of electricity load shedding in Nepal. Renew. Sustain. Energy Rev. 2021 , 146 , 111112. [ Google Scholar ] [ CrossRef ]
• Hashemi, M.; Jenkins, G.P.; Jyoti, R.; Ozbafli, A. Evaluating the cost to industry of electricity outages. Energy Sources, Part B Econ. Planning, Policy 2018 , 13 , 340–349. [ Google Scholar ] [ CrossRef ]
• Hashemi, M. The economic value of unsupplied electricity: Evidence from Nepal. Energy Econ. 2021 , 95 , 105124. [ Google Scholar ] [ CrossRef ]
• Apenteng, B.A.; Opoku, S.T.; Ansong, D.; Akowuah, E.A.; Afriyie-Gyawu, E. The effect of power outages on in-facility mortality in healthcare facilities: Evidence from Ghana. Glob. Public Health 2018 , 13 , 545–555. [ Google Scholar ] [ CrossRef ]
• Twerefou, D.K. Willingness to pay for improved electricity supply in ghana. Mod. Econ. 2014 , 5 , 489–498. [ Google Scholar ] [ CrossRef ]
• Merem, E.C.; Twumasi, Y.; Wesley, J.; Isokpehi, P.; Fageir, S.; Crisler, M.; Romorno, C.; Hines, A.; Ochai, G.S.; Leggett, S.; et al. Assessing renewable energy use in ghana: The case of the electricity sector. Energy Power 2018 , 8 , 16–34. [ Google Scholar ] [ CrossRef ]
• Emenike, D. A Qualitative Case Study of Nigeria Electric Power Outage and Its Economic Consequence. ProQuest Dissertations and Theses. 2016. Available online: https://www.proquest.com/openview/6d308d7a1d5db3b7e994b94fafd860ab/1?pq-origsite=gscholar&cbl=18750 (accessed on 8 June 2023).
• Amadi, H.N. Power outages in Portharcourt city: Problems and solutions. IOSR J. Electr. Electron. Eng. Ver. III. 2015 , 10 , 59–66. [ Google Scholar ]
• Akuru, U.B.; Okoro, O.I. Economic implications of constant power outages on SMEs in Nigeria. J. Energy S. Afr. 2014 , 25 , 61–66. [ Google Scholar ] [ CrossRef ]
• Airoboman, A.E.; Amaize, P.A.; Ibhaze, A.E.; Ayo, O.O. Economic implication of power outage in Nigeria: An industrial review. Int. J. Appl. Eng. Res. 2016 , 11 , 4930–4933. [ Google Scholar ]
• Moyo, B. Power infrastructure quality and manufacturing productivity in Africa: A firm level analysis. Energy Policy 2013 , 61 , 1063–1070. [ Google Scholar ] [ CrossRef ]
• Arlet, J. Electricity Sector Constraints for Firms Across Economies: A Comparative Analysis. Doing Business Research Notes, World Bank Malaysia Hub. 2017. Available online: https://documents1.worldbank.org/curated/en/409771499690745091/pdf/Electricity-sector-constraints-for-firms-across-economies-a-comparative-analysis.pdf (accessed on 8 June 2023).
• The Biggest Losers Worldwide from Power Outages/Generac Power Systems. (n.d.). Available online: https://www.generac.com/be-prepared/power-outages/power-outage-financial-losses (accessed on 5 March 2023).
• Amin, M.; Bernell, D. Power sector reform in Afghanistan: Barriers to achieving universal access to electricity. Energy Policy 2018 , 123 , 72–82. [ Google Scholar ] [ CrossRef ]
• How to Solve Iraq’s Hellishly Hot Power Crisis–DW–07/08/2021. (n.d.). Available online: https://www.dw.com/en/why-are-iraqs-electricity-issues-so-hard-to-solve/a-58189500 (accessed on 9 March 2023).
• Oil-Rich IRAQ Grapples with Power Outages for 30 years. (n.d.). Available online: https://www.aa.com.tr/en/middle-east/oil-rich-iraq-grapples-with-power-outages-for-30-years/2297835 (accessed on 9 March 2023).
• Power Outages in Firms in a Typical Month (Number)/Data. (n.d.). Available online: https://data.worldbank.org/indicator/IC.ELC.OUTG (accessed on 1 June 2023).
• Power Outages in Firms in a Typical Month. 2020. (n.d.) Available online: https://ourworldindata.org/grapher/power-outages-in-firms-per-month (accessed on 9 March 2023).
• Gelazanskas, L.; Gamage, K.A. Demand side management in smart grid: A review and proposals for future direction. Sustain. Cities Soc. 2014 , 11 , 22–30. [ Google Scholar ] [ CrossRef ]
• Behrangrad, M. A review of demand side management business models in the electricity market. Renew. Sustain. Energy Rev. 2015 , 47 , 270–283. [ Google Scholar ] [ CrossRef ]
• Eissa, M. Demand side management program evaluation based on industrial and commercial field data. Energy Policy 2011 , 39 , 5961–5969. [ Google Scholar ] [ CrossRef ]
• Warren, P. A review of demand-side management policy in the UK. Renew. Sustain. Energy Rev. 2014 , 29 , 941–951. [ Google Scholar ] [ CrossRef ]
• Lampropoulos, I.; Kling, W.L.; Ribeiro, P.F.; Berg, J.V.D. History of demand side management and classification of demand response control schemes. In Proceedings of the 2013 IEEE Power & Energy Society General Meeting, Vancouver, BC, Canada, 21–25 July 2013. [ Google Scholar ]
• Pattanaik, P.A.; Sahoo, N.; Mishra, S. Demand side management in smart grid: A laboratory-based educational perspective. Int. J. Electr. Eng. Educ. 2021 , 58 , 331–356. [ Google Scholar ] [ CrossRef ]
• Albadi, M.H.; El-Saadany, E.F. Demand response in electricity markets: An overview. In Proceedings of the 2007 IEEE Power Engineering Society General Meeting, Tampa, FL, USA, 24–28 June 2007; pp. 1–5. [ Google Scholar ] [ CrossRef ]
• Palensky, P.; Dietrich, D. Demand side management: Demand response, intelligent energy systems, and smart loads. IEEE Trans. Ind. Informatics 2011 , 7 , 381–388. [ Google Scholar ] [ CrossRef ]
• Bjarghov, S.; Loschenbrand, M.; Ibn Saif, A.U.N.; Pedrero, R.A.; Pfeiffer, C.; Khadem, S.K.; Rabelhofer, M.; Revheim, F.; Farahmand, H. Developments and challenges in local electricity markets: A comprehensive review. IEEE Access 2021 , 9 , 58910–58943. [ Google Scholar ] [ CrossRef ]
• Atia, R.; Yamada, N. Sizing and analysis of renewable energy and battery systems in residential microgrids. IEEE Trans. Smart Grid 2016 , 7 , 1204–1213. [ Google Scholar ] [ CrossRef ]
• Tang, W.; Bi, S.; Zhang, Y.J. Online charging scheduling algorithms of electric vehicles in smart grid: An overview. IEEE Commun. Mag. 2016 , 54 , 76–83. [ Google Scholar ] [ CrossRef ]
• Calvillo, C.; Sánchez-Miralles, A.; Villar, J. Energy management and planning in smart cities. Renew. Sustain. Energy Rev. 2016 , 55 , 273–287. [ Google Scholar ] [ CrossRef ]
• Debnath, R.; Kumar, D.; Mohanta, D.K. Effective demand side management (DSM) strategies for the deregulated market envioronments. In Proceedings of the 2017 Conference on Emerging Devices and Smart Systems (ICEDSS), Mallasamudram, India, 3–4 March 2017; pp. 110–115. [ Google Scholar ] [ CrossRef ]
• Rocha, H.R.; Honorato, I.H.; Fiorotti, R.; Celeste, W.C.; Silvestre, L.J.; Silva, J.A. An Artificial Intelligence based scheduling algorithm for demand-side energy management in Smart Homes. Appl. Energy 2021 , 282 , 116145. [ Google Scholar ] [ CrossRef ]
• Wang, Y.; Liu, L.; Wennersten, R.; Sun, Q. Peak shaving and valley filling potential of energy management system in high-rise residential building. Energy Procedia 2019 , 158 , 6201–6207. [ Google Scholar ] [ CrossRef ]
• Ioakimidis, C.S.; Thomas, D.; Rycerski, P.; Genikomsakis, K.N. Peak shaving and valley filling of power consumption profile in non-residential buildings using an electric vehicle parking lot. Energy 2018 , 148 , 148–158. [ Google Scholar ] [ CrossRef ]
• Agamah, S.U.; Ekonomou, L. Peak demand shaving and load-levelling using a combination of bin packing and subset sum algorithms for electrical energy storage system scheduling. IET Sci. Meas. Technol. 2016 , 10 , 477–484. [ Google Scholar ] [ CrossRef ]
• Buja, G.; Bertoluzzo, M.; Fontana, C. Reactive power compensation capabilities of V2G-enabled electric vehicles. IEEE Trans. Power Electron. 2017 , 32 , 9447–9459. [ Google Scholar ] [ CrossRef ]
• Jabir, H.J.; Teh, J.; Ishak, D.; Abunima, H. Impacts of demand-side management on electrical power systems: A review. Energies 2018 , 11 , 1050. [ Google Scholar ] [ CrossRef ]
• Bhatt, P.; Long, C.; Saiyad, M. Review of the impact of vehicle-to-grid schemes on electrical power systems. In Advances in Electric Power and Energy Infrastructure ; Lecture Notes in Electrical Engineering; Springer: Cham, Switzerland, 2020; pp. 199–208. [ Google Scholar ] [ CrossRef ]
• Balasubramanian, S.; Balachandra, P. Characterising electricity demand through load curve clustering: A case of Karnataka electricity system in India. Comput. Chem. Eng. 2021 , 150 , 107316. [ Google Scholar ] [ CrossRef ]
• Masike, O. A literature review on demand side and energy efficient management. Int. J. Curr. Trends Eng. Res. 2016 , 2 , 131–137. [ Google Scholar ]
• Kagiannas, A.G.; Didis, T.; Askounis, D.T.; Psarras, J. Strategic appraisal of energy models for Mozambique. Int. J. Energy Res. 2003 , 27 , 173–186. [ Google Scholar ] [ CrossRef ]
• Gärttner, J.; Flath, C.M.; Weinhardt, C. Portfolio and contract design for demand response resources. Eur. J. Oper. Res. 2018 , 266 , 340–353. [ Google Scholar ] [ CrossRef ]
• Luo, T.; Ault, G.; Galloway, S. Demand side management in a highly decentralized energy future. In Proceedings of the Universities Power Engineering Conference (UPEC), 2010 45th International, Cardiff, UK, 31 August–3 September 2010. [ Google Scholar ]
• Sharma, A.K.; Saxena, A. A demand side management control strategy using Whale optimization algorithm. SN Appl. Sci. 2019 , 1 , 870. [ Google Scholar ] [ CrossRef ]
• Gellings, C. The concept of demand-side management for electric utilities. Proc. IEEE 1985 , 73 , 1468–1470. [ Google Scholar ] [ CrossRef ]
• Arteconi, A.; Polonara, F. Assessing the demand side management potential and the energy flexibility of heat pumps in buildings. Energies 2018 , 11 , 1846. [ Google Scholar ] [ CrossRef ]
• Ramesh, M.; Saini, R.P. Demand Side Management based techno-economic performance analysis for a stand-alone hybrid renewable energy system of India. Energy Sources Part A Recover. Util. Environ. Eff. 2020 , 1–29. [ Google Scholar ] [ CrossRef ]
• Tapsuwan, S.; Peña-Arancibia, J.L.; Lazarow, N.; Albisetti, M.; Zheng, H.; Rojas, R.; Torres-Alferez, V.; Chiew, F.H.; Hopkins, R.; Penton, D.J. A benefit cost analysis of strategic and operational management options for water management in hyper-arid southern Peru. Agric. Water Manag. 2022 , 265 , 107518. [ Google Scholar ] [ CrossRef ]
• Peng, P.; Li, Y.; Li, D.; Guan, Y.; Yang, P.; Hu, Z.; Zhao, Z.; Liu, D. Optimized economic operation strategy for distributed energy storage with multi-profit mode. IEEE Access 2021 , 9 , 8299–8311. [ Google Scholar ] [ CrossRef ]
• Anwar, M.B.; Qazi, H.W.; Burke, D.J.; O’Malley, M.J. Harnessing the flexibility of demand-side resources. IEEE Trans. Smart Grid 2019 , 10 , 4151–4163. [ Google Scholar ] [ CrossRef ]
• Tong, Z.; Cheng, Z.; Tong, S. A review on the development of compressed air energy storage in China: Technical and economic challenges to commercialization. Renew. Sustain. Energy Rev. 2021 , 135 , 110178. [ Google Scholar ] [ CrossRef ]
• Ly, A.; Bashash, S. Fast transactive control for frequency regulation in smart grids with demand response and energy storage. Energies 2020 , 13 , 4771. [ Google Scholar ] [ CrossRef ]
• Ding, Y.; Xu, Q.; Xia, Y.; Zhao, J.; Yuan, X.; Yin, J. Optimal dispatching strategy for user-side integrated energy system considering multiservice of energy storage. Int. J. Electr. Power Energy Syst. 2021 , 129 , 106810. [ Google Scholar ] [ CrossRef ]
• Longe, O.M.; Ouahada, K.; Rimer, S.; Ferreira, H.C.; Vinck, A.J.H. Distributed optimisation algorithm for demand side management in a grid-connected smart microgrid. Sustainability 2017 , 9 , 1088. [ Google Scholar ] [ CrossRef ]
• Diller, J.; Idowu, P.; Khazaei, J. Load-Leveling Trainer for Demand Side Management on a 45kW Cyber-Physical Microgrid. In Proceedings of the 2020 IEEE Texas Power and Energy Conference (TPEC), College Station, TX, USA, 6–7 February 2020; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Puttamadappa, C.; Parameshachari, B.D. Demand side management of small scale loads in a smart grid using glow-worm swarm optimization technique. Microprocess. Microsystems 2019 , 71 , 102886. [ Google Scholar ] [ CrossRef ]
• Martinez-Godoy, J.L.; Martell-Chavez, F.; Sanchez-Chavez, I.Y.; Castillo-Velasquez, F.A.; Torres-Falcon, M.D.C.P. A peak demand control algorithm for multiple controllable loads in industrial processes. IEEE Access 2021 , 9 , 116315–116325. [ Google Scholar ] [ CrossRef ]
• Mediwaththe, C.P.; Stephens, E.R.; Smith, D.B.; Mahanti, A. A dynamic game for electricity load management in neighborhood area networks. IEEE Trans. Smart Grid 2016 , 7 , 1329–1336. [ Google Scholar ] [ CrossRef ]
• Logenthiran, T.; Srinivasan, D.; Vanessa, K.W.M. Demand side management of smart grid: Load shifting and incentives. J. Renew. Sustain. Energy 2014 , 6 , 033136. [ Google Scholar ] [ CrossRef ]
• Li, C.; Yu, X.; Yu, W.; Chen, G.; Wang, J. Efficient computation for sparse load shifting in demand side management. IEEE Trans. Smart Grid 2017 , 8 , 250–261. [ Google Scholar ] [ CrossRef ]
• Sharda, S.; Singh, M.; Sharma, K. Demand side management through load shifting in IoT based HEMS: Overview, challenges and opportunities. Sustain. Cities Soc. 2021 , 65 , 102517. [ Google Scholar ] [ CrossRef ]
• Zeeshan, M.; Jamil, M. Adaptive moth flame optimization based load shifting technique for demand side management in smart grid. IETE J. Res. 2022 , 68 , 778–789. [ Google Scholar ] [ CrossRef ]
• Jamil, M.; Mittal, S. Hourly load shifting approach for demand side management in smart grid using grasshopper optimisation algorithm. IET Gener. Transm. Distrib. 2020 , 14 , 808–815. [ Google Scholar ] [ CrossRef ]
• Fernandez, J.M.R.; Payan, M.B.; Santos, J.M.R. The merit-order effect of load-shifting: An estimate for the spanish market. Sci. J. Riga Tech. Univ. Environ. Clim. Technol. 2020 , 24 , 43–57. [ Google Scholar ] [ CrossRef ]
• Sathiya, S. Demand side management of renewable energy integrated smart grid using load shifting techniques. J. Crit. Rev. 2020 , 3193–3199. [ Google Scholar ] [ CrossRef ]
• Hirmiz, R.; Teamah, H.; Lightstone, M.; Cotton, J. Performance of heat pump integrated phase change material thermal storage for electric load shifting in building demand side management. Energy Build. 2019 , 190 , 103–118. [ Google Scholar ] [ CrossRef ]
• López, M.A.; de la Torre, S.; Martín, S.; Aguado, J.A. Demand-side management in smart grid operation considering electric vehicles load shifting and vehicle-to-grid support. Int. J. Electr. Power Energy Syst. 2015 , 64 , 689–698. [ Google Scholar ] [ CrossRef ]
• Mohamed, A.; Khan, M.T. A review of electrical energy management techniques: Supply and consumer side (industries). J. Energy S. Afr. 2009 , 20 , 14–21. [ Google Scholar ] [ CrossRef ]
• Tutkun, N.; Ungoren, F.; Alpagut, B. Improved load shifting and valley filling strategies in demand side management in a nano scale off-grid wind-PV system in remote areas. In Proceedings of the 2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC), Calabria, Italy, 16–18 May 2017; pp. 13–18. [ Google Scholar ] [ CrossRef ]
• Shi, P.; Li, Y.; Chen, Z.; Shu, J.; Hu, X. Economic benefit assessment of multi-type flexible demand side resources paticipating in valley-filling market. In Proceedings of the 2020 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), Weihai, China, 13–15 July 2020; pp. 227–233. [ Google Scholar ] [ CrossRef ]
• Zhu, M.; Ji, Y.; Ju, W.; Gu, X.; Liu, C.; Xu, Z. A business service model of smart home appliances participating in the peak shaving and valley filling based on cloud platform. IEICE Trans. Inf. Syst. 2021 , 104 , 1185–1194. [ Google Scholar ] [ CrossRef ]
• Barzkar, A.; Hosseini, S.M.H. A novel peak load shaving algorithm via real-time battery scheduling for residential distributed energy storage systems. Int. J. Energy Res. 2018 , 42 , 2400–2416. [ Google Scholar ] [ CrossRef ]
• Ibrik, I. Modeling the optimum solar PV system for management of peak demand. Int. J. Energy Econ. Policy 2019 , 9 , 246–250. [ Google Scholar ] [ CrossRef ]
• Arnaudo, M.; Topel, M.; Puerto, P.; Widl, E.; Laumert, B. Heat demand peak shaving in urban integrated energy systems by demand side management—A techno-economic and environmental approach. Energy 2019 , 186 , 115887. [ Google Scholar ] [ CrossRef ]
• Guelpa, E.; Verda, V. Demand response and other demand side management techniques for district heating: A review. Energy 2021 , 219 , 119440. [ Google Scholar ] [ CrossRef ]
• Lizondo, D.; Araujo, P.; Will, A.; Rodriguez, S. Multiagent model for distributed peak shaving system with demand-side management approach. In Proceedings of the 2017 First IEEE International Conference on Robotic Computing (IRC), Taichung, Taiwan, 10–12 April 2017; pp. 352–357. [ Google Scholar ] [ CrossRef ]
• Ibrahim, O.; Bakare, M.S.; Amosa, T.I.; Otuoze, A.O.; Owonikoko, W.O.; Ali, E.M.; Adesina, L.M.; Ogunbiyi, O. Development of fuzzy logic-based demand-side energy management system for hybrid energy sources. Energy Convers. Manag. X 2023 , 18 , 100354. [ Google Scholar ] [ CrossRef ]
• Karimi, H.; Jadid, S. Multi-layer energy management of smart integrated-energy microgrid systems considering generation and demand-side flexibility. Appl. Energy 2023 , 339 , 120984. [ Google Scholar ] [ CrossRef ]
• Sharma, A.K.; Saxena, A.; Palwalia, D.K. Impact of divergence in BBO on efficient energy strategy of demand side management. Technol. Econ. Smart Grids Sustain. Energy 2022 , 7 , 28. [ Google Scholar ] [ CrossRef ]
• Kalpana, D.R.; NageshaRao, S.H.; Siddaiah, R.; Mala, R. Case study on demand side management-based cost optimized battery integrated hybrid renewable energy system for remote rural electrification. Energy Storage 2022 , 5 , e410. [ Google Scholar ] [ CrossRef ]
• Ullah, K.; Khan, T.A.; Hafeez, G.; Khan, I.; Murawwat, S.; Alamri, B.; Ali, F.; Ali, S.; Khan, S. Demand side management strategy for multi-objective day-ahead scheduling considering wind energy in smart grid. Energies 2022 , 15 , 6900. [ Google Scholar ] [ CrossRef ]
• Yaghmaee, M.H.; Moghaddassian, M.; Leon-Garcia, A. Autonomous two-tier cloud-based demand side management approach with microgrid. IEEE Trans. Ind. Informatics 2017 , 13 , 1109–1120. [ Google Scholar ] [ CrossRef ]
• Martirano, L.; Habib, E.; Parise, G.; Greco, G.; Manganelli, M.; Massarella, F.; Parise, L. Demand side management in microgrids for load control in nearly zero energy buildings. IEEE Trans. Ind. Appl. 2017 , 53 , 1769–1779. [ Google Scholar ] [ CrossRef ]
• Arasteh, F.; Riahy, G.H. MPC-based approach for online demand side and storage system management in market based wind integrated power systems. Int. J. Electr. Power Energy Syst. 2019 , 106 , 124–137. [ Google Scholar ] [ CrossRef ]
• Craparo, E.; Sprague, J. Integrated supply- and demand-side energy management for expeditionary environmental control. Appl. Energy 2019 , 233–234 , 352–366. [ Google Scholar ] [ CrossRef ]
• Saki, R.; Kianmehr, E.; Rokrok, E.; Doostizadeh, M.; Khezri, R.; Shafie-Khah, M. Interactive Multi-level planning for energy management in clustered microgrids considering flexible demands. Int. J. Electr. Power Energy Syst. 2022 , 138 , 107978. [ Google Scholar ] [ CrossRef ]
• Ahmarinejad, A. A multi-objective optimization framework for dynamic planning of energy hub considering integrated demand response program. Sustain. Cities Soc. 2021 , 74 , 103136. [ Google Scholar ] [ CrossRef ]
• Deveci, K.; Güler, A. CMOPSO based multi-objective optimization of renewable energy planning: Case of Turkey. Renew. Energy 2020 , 155 , 578–590. [ Google Scholar ] [ CrossRef ]
• Mohseni, S.; Brent, A.C.; Kelly, S.; Browne, W.N. Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review. Renew. Sustain. Energy Rev. 2022 , 158 , 112095. [ Google Scholar ] [ CrossRef ]
• Fan, H.; Lu, J.; Li, Z.; Shahidehpour, M.; Zhang, S. Optimal planning of integrated electricity-gas system with demand side management. IEEE Access 2019 , 7 , 176790–176798. [ Google Scholar ] [ CrossRef ]
• Awan, M.M.A.; Javed, M.Y.; Asghar, A.B.; Ejsmont, K.; Rehman, Z.U. Economic integration of renewable and conventional power sources—A case study. Energies 2022 , 15 , 2141. [ Google Scholar ] [ CrossRef ]
• Park, H.; Kim, J.-K.; Yi, S.C. Optimization of site utility systems for renewable energy integration. Energy 2023 , 269 , 126799. [ Google Scholar ] [ CrossRef ]
• Iraq Energy Information/Enerdata. (n.d.). Available online: https://www.enerdata.net/estore/energy-market/iraq/ (accessed on 1 March 2023).
• Statistical Review of World Energy/Energy Economics/Home. (n.d.). Available online: https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html (accessed on 15 September 2023).
• Electricity Sector in Iraq–Wikipedia. (n.d.). Available online: https://en.wikipedia.org/wiki/Electricity_sector_in_Iraq (accessed on 15 September 2023).
• Iraq Needs Renewables, but They Won’t Solve Its Power Problems without Broader Reforms/Middle East Institute. (n.d.). Available online: https://www.mei.edu/publications/iraq-needs-renewables-they-wont-solve-its-power-problems-without-broader-reforms (accessed on 15 September 2023).
• UNDG Iraq Trust Fund. (n.d.). Available online: https://mptf.undp.org/fund/itf00 (accessed on 15 September 2023).
• World Energy Outlook 2022–Analysis–IEA. (n.d.). Available online: https://www.iea.org/reports/world-energy-outlook-2022 (accessed on 15 September 2023).
• Abu Dhabi’s Masdar Signs up for 1GW Solar In Iraq/MEES. (n.d.). Available online: https://www.mees.com/2021/10/8/corporate/abu-dhabis-masdar-signs-up-for-1gw-solar-in-iraq/0dfe37d0-282f-11ec-a09c-db0536a900e5 (accessed on 15 September 2023).
• Heatwaves Scorch Iraq as Protracted Political Crisis Grinds on/News/Al Jazeera. (n.d.). Available online: https://www.aljazeera.com/news/2022/8/6/heatwaves-scorch-iraq-as-protracted-political-crisis-grinds-on (accessed on 15 September 2023).
• Iraq-GCC Power Link Set For 2024, While Saudi Talks Advance. (n.d.). Available online: https://www.mees.com/2022/7/22/power-water/iraq-gcc-power-link-set-for-2024-while-saudi-talks-advance/f63f1380-09af-11ed-ba8f-c3cdbd9848c6 (accessed on 15 September 2023).
• Iraq’s Power Sector: Problems and Prospects—Georgetown Journal of International Affairs. (n.d.). Available online: https://gjia.georgetown.edu/2020/01/13/iraqs-power-sector-problems-and-prospects/ (accessed on 18 August 2023).
• Power outage—Wikipedia. (n.d.). Available online: https://en.wikipedia.org/wiki/Power_outage (accessed on 18 August 2023).
• Nduhuura, P.; Garschagen, M.; Zerga, A. Impacts of Electricity Outages in Urban Households in Developing Countries: A Case of Accra, Ghana. Energies 2021 , 14 , 3676. [ Google Scholar ] [ CrossRef ]
• Gillingham, K.T.; Knittel, C.R.; Li, J.; Ovaere, M.; Reguant, M. The short-run and long-run effects of COVID-19 on energy and the environment. Joule 2020 , 4 , 1337–1341. [ Google Scholar ] [ CrossRef ]
• Sakah, M.; Can, S.d.l.R.d.; Diawuo, F.A.; Sedzro, M.D.; Kuhn, C. A study of appliance ownership and electricity consumption determinants in urban Ghanaian households. Sustain. Cities Soc. 2019 , 44 , 559–581. [ Google Scholar ] [ CrossRef ]
• Praktiknjo, A.J.; Hähnel, A.; Erdmann, G. Assessing energy supply security: Outage costs in private households. Energy Policy 2011 , 39 , 7825–7833. [ Google Scholar ] [ CrossRef ]
• Newswire, P.R. Global Demand Response (DR) Industry ; Reportlinker: Lyon, France, 2016. [ Google Scholar ]
• Al-Salim, K.; Andonovic, I.; Michie, C. Cyclic blackout mitigation and prevention using semi-dispatchable standby generation and stratified demand dispatch. Sustain. Energy Grids Networks 2015 , 4 , 29–42. [ Google Scholar ] [ CrossRef ]
• Lv, Z.; Wang, L.; Guan, Z.; Wu, J.; Du, X.; Zhao, H.; Guizani, M. An optimizing and differentially private clustering algorithm for mixed data in SDN-based smart grid. IEEE Access 2019 , 7 , 45773–45782. [ Google Scholar ] [ CrossRef ]
• Leardini, P.; Manfredini, M.; Callau, M. Energy upgrade to Passive House standard for historic public housing in New Zealand. Energy Build. 2015 , 95 , 211–218. [ Google Scholar ] [ CrossRef ]

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Salman, H.M.; Pasupuleti, J.; Sabry, A.H. Review on Causes of Power Outages and Their Occurrence: Mitigation Strategies. Sustainability 2023 , 15 , 15001. https://doi.org/10.3390/su152015001

Salman HM, Pasupuleti J, Sabry AH. Review on Causes of Power Outages and Their Occurrence: Mitigation Strategies. Sustainability . 2023; 15(20):15001. https://doi.org/10.3390/su152015001

Salman, Hasan M., Jagadeesh Pasupuleti, and Ahmad H. Sabry. 2023. "Review on Causes of Power Outages and Their Occurrence: Mitigation Strategies" Sustainability 15, no. 20: 15001. https://doi.org/10.3390/su152015001

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21 August 2024

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When Max Kanter bought an electric vehicle back in 2022 , he didn’t expect it to be so hard to find accurate data on the cost and carbon-intensity of the electricity surging through the power grid.

As not only a new EV owner but also a data whiz, he sought out the information because he ​ “ wanted to build a machine learning algorithm to check energy prices and charge and discharge profitably,” Kanter told Canary Media. ​ “ But when I got a peek behind the curtain, I saw the data and tools the industry had could be a lot better.”

That’s why Kanter — who has previously built and sold an analytics startup — co-founded Grid Status , a data platform that aims to make high-quality, real-time grid information widely accessible.

The platform, launched last year, grew out of Kanter’s early efforts to pull together real-time grid data, the results of which he posted to the open-source software development platform GitHub so that ​ “ anyone could download our data for free and start using it,” he said. The GitHub post gained traction among some in the energy industry — and helped Kanter meet his eventual Grid Status co-founders, longtime energy industry players Connor Waldoch and Andrew Gelston.

Since starting Grid Status, Kanter and the rest of his seven-member team have seen demand for their combination of free data and subscription services increase to about 10 , 000 users per month. Those users include most of the country’s interstate grid operators and largest energy project developers, as well as some well-known U.S. energy experts.

“ We’ve taken the approach to democratizing access to data on the grid, and we’ve signed up people from all corners of the industry,” said Kanter, who serves as the company’s CEO .

On Wednesday, Grid Status announced an $ 8 million investment round led by Energize Capital , a venture firm backed by General Electric, Schneider Electric, and major energy developer Invenergy. Other investors include former GitHub CEO Nat Friedman and Daniel Gross of NFDG Ventures , and Rayburn Electric Cooperative , a member-owned utility in northeast Texas that’s using Grid Status’ data and algorithms in its grid control room.

Rayburn is one of the growing number of Grid Status customers that are paying the company to co-develop the products they need to track what’s happening on the grid, said Tyler Lancaster, a partner at Energize.

“ Data centers, virtual power plants, consumer-electricity-oriented companies — there are hundreds of thousands of parties that need to understand the grid, and do so in a much more technology-forward manner,” he said. ​ “ If Grid Status can serve that vision, we’re talking about a much more valuable enterprise down the road.”

Other Grid Status users are tapping into the company’s free data resources, which include dashboards and graphing tools that allow users to track and analyze various grid metrics nationwide, from record-high renewables generation to pricing. The company’s data has been featured in reporting by The New York Times , The Wall Street Journal , CNBC , and other publications — including Canary Media — and is a regular source of data for energy analysts’ social media posts .

“ It’s in the public interest to have a tool like Grid Status that provides a valuable service — one place where you can go and get a consistent dashboard of what’s going on,” said Ric O’Connell, founding executive director of nonprofit analysis group GridLab, which provided financial support for some of Grid Status’s early-stage work. 

Why is grid data so hard to get and use? 

Kanter’s past work in general-purpose machine learning gave him access to lots of different kinds of data. ​ “ But one we never touched on was energy. I think that’s because it’s an esoteric domain, and having data, but not understanding how that data is used, isn’t very useful.”

O’Connell agreed that accessing and using the data available from grid operators and government agencies is ​ “ incredibly complicated. Right now you could go dig around on their web pages and find where they post these data. But it would take you a long time, and every place is a little bit different — different formats and different ways of representing it.”

Kanter cited the example of ERCOT , the grid operator for most of Texas. ​ “ If you dig deep enough on ERCOT ’s site, there’s a place you can find — with some delay — what resources are being used” to generate power, he said. But that data comes in a zip file, which itself contains eight different files, and ​ “ you have to merge them all together,” he added. ​ “ Then, if you want to figure out what zone they are in, you have to merge them with another dataset — and if you want to know the prices, that’s another dataset.”

Grid operators like ERCOT and government agencies like the U.S. Energy Information Administration ​ “ do a very respectable job making a lot of this data available,” he noted, but it can be hard to navigate. Collecting, validating, merging, and regularly updating these various datasets makes the information much more useful, Kanter said.

“ What we hear from many of our customers is they go from a universe with 10 tabs open on their computer to just being able to go to Grid Status.”

David A. Naylor, CEO of Rayburn Electric Cooperative, agreed that collecting this real-time data in one dashboard has been valuable for his organization, which operates transmission and generation for four distribution cooperatives that serve over 575 , 000 Texans. The member-owned utility was hard-hit by the massive grid outages and energy market price spikes during Winter Storm Uri in 2021 , and had been working to improve its understanding of the ups and downs of the increasingly stressed-out ERCOT  grid.

“ The real-time feedback loop was what was really lacking,” he said. ​ “ Our operators and power supply folks are looking at real time renewable mix, solar as well as wind. They’re also looking at the reserve capacity, so they can see if we’re getting close to a load shed event or not. And they’re tracking both transmission outages and resource outages” — power lines or power plants that unexpectedly shut down — ​ “ because they have an impact on prices.”

To collect that data, Naylor said, ​ “ we could look at some of the ERCOT dashboards, but those can be kind of overwhelming — and they’re all over the place.” Rayburn started to work on developing its own tools to bring these data sources together, but ​ “ when we ran across Grid Status, we noticed how seamless it was, how fast it updated. It made a lot of sense for us to pivot.”

Rayburn had engaged in discussions with some other providers of commercial data products that supply this kind of real-time information, he noted. But ​ “ the ability to tailor it and include our own data was cumbersome, or discouraged.”

Kanter also highlighted this difference in approach between Grid Status and the various commercial providers of real-time consolidated grid data, which tend to be focused on serving larger and more richly resourced utilities, independent power plant operators, and energy traders.

“ One of the enablers of what we see as our long-term value is that we have pretty open doors for anyone who wants access to this data,” he said. ​ “ We’re not just restricting it to the very highest value use cases.”

Much of the work that Grid Status has turned into paying relationships started with users experimenting with its open-source data and application programming interfaces (APIs), Kanter said. ​ “ People can try our product out for free before signing up for the paid version. That lets them validate we have the data they need, that our performance standards are up to theirs.”

Where Grid Status is going next

The company’s new funding should help it expand work on its latest product — one O’Connell is particularly excited about: ​ “ this really awesome nodal price map, where you can see where in the country the grid is stressed.”

The map is still in the beta testing stage, but Kanter said it’s ​ “ something we wanted to build since day one. It’s one of the most intuitive things for someone to get a grasp on regarding the complexity of the grid.” 

Each dot on the map corresponds to a node on a transmission grid at which a locational marginal price ( LMP ) for power is set in 5 -minute to 15 -minute intervals. This map is useful to power generators, energy traders, grid planners, and other energy industry actors who need price information — but it can also indicate where lack of transmission capacity or electricity supply is putting specific parts of the grid under stress.

Grid Status has put a lot of work into securing and updating the various data sources required to capture LMPs at 20 , 000 nodes across the continental U.S. ​ “ If you just want the fuel mix for one region of the country, you can build that one-off data source,” Kanter said. ​ “ But the moment you need to combine 10 different sets of data, and recreate it and visualize it — and conduct high-performance querying of that data so it’s fast — that’s transformative for many industries.”

Now that the legwork is done, the company is looking at what it can do next with what it’s built, he said. ​ “ We want to add more tools for aggregating what’s happening on the map,” such as overlaying data on the transmission lines and substations connecting them. That could potentially help explain why two nodes that are close to each other geographically may be experiencing wildly different pricing, for example, possibly pointing to a need to build more power lines that could alleviate the problem.

From the perspective of GridLab’s O’Connell, the availability of open-sourced, real-time data like this new map — and other Grid Status offerings — is critical to understanding how the power grid is changing as more and more renewables come online.

To date, efforts to open-source grid data have focused on historical information, like the datasets developed by the worker-owned cooperative Catalyst Cooperative , which has helped inform research into grid planning and carbon emissions impacts , he noted.

The real-time data Grid Status deals with is harder to access in comparison, he said — but it also makes it much easier for analysts, journalists, and clean-energy advocates to understand complex grid issues as they unfold. That includes the role that renewable energy can play in making the grid more resilient in the face of extreme weather, for example.

In fact, O’Connell learned about Kanter’s early work while doing research with Alison Silverstein, an energy analyst and former adviser to the Public Utility Commission of Texas and the Federal Energy Regulatory Commission, on the role of different generation resources during the Winter Storm Uri grid disaster in Texas.

Amid the crisis, Republican politicians in Texas attempted to cast blame on frozen wind turbines for the loss of generation capacity that forced the state to cut off power for millions of Texans during a week of subzero temperatures. But the data quickly revealed that the primary culprits were cold-weather-related failures at fossil gas wells, pipelines, and power plants.

“ We wanted a good source of information that was clear and easy to understand what was really going on,” O’Connell said. ​ “ We started to scope out tools — and then it turns out that Max had already built them.”

Clean energy

Jeff St. John is director of news and special projects at Canary Media. He covers innovative grid technologies, rooftop solar and batteries, clean hydrogen, EV charging, and more.

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Power underwhelming: Why are there power outages?

Special report.

By Mark T. Amoguis Senior Researcher

IN THE PHILIPPINES, one would have to get used to brownouts, or the drop in voltage in an electrical power supply system. Whether or not it is intentional, these outages have wide-ranging effects on the economy: households would experience no electricity for a few minutes or even for hours, causing great inconvenience; businesses would incur higher costs by way of lost revenue and reduced productivity; and investors would be hesitant to do business, leading to reduced investments.

The Luzon grid has had episodes of “yellow” alerts since March due to high electricity demand outstripping supply as well as unscheduled outages of power plants. The first yellow alert, which occurred on March 5, saw peak demand for the day reaching 9,491 megawatts (MW) against the grid’s available capacity of 10,115 MW with an operating margin at just 624 MW — falling short of the required contingency reserve of 647 MW.

NGCP, which is the private firm that operates, maintains, and develops the country’s transmission network, issues these alerts whenever energy reserves are inadequate. The grid operator has several levels of reserve energy that it uses to stabilize the fluctuating power demanded from the electricity grid.

One, there is a “regulating” reserve, which is the standard operating requirement to maintain a balance between available capacity and system demand. This is ideally equivalent to around four percent of peak demand.

On top of the regulating reserve, the NGCP maintains a “contingency” reserve that it allocates to immediately cover the loss in supply when the largest power generating unit online — usually at around 600 MW — fails to deliver.

Lastly, the operator also maintains a “dispatchable” reserve that is readily available to replenish lost contingency reserve.

A yellow alert notice is issued when the dispatchable reserve is fully spent and the system is already tapping into its contingency reserve. A red alert notice means both dispatchable and contingency reserves are gone.

Based on NGCP notices, there were seven yellow alerts and seven red alerts in April alone. In May, there were 13 yellow alerts and two red alerts.

This number far outstripped the number of yellow alerts in the previous years, according to consumer advocacy group CitizenWatch Philippines’ “PowerPlant Watch.”

“Comparing this to previous years, we had only seven instances of yellow alerts in 2018 and only three during the same period in 2017,” wrote Hannah Viola, convenor of CitizenWatch and energy fellow at Stratbase ADR Institute, in her column in BusinessWorld titled “A Call for Energy Transparency” published on April 9.

Bienvenido S. Oplas, Jr., columnist for BusinessWorld , economist, and president of Minimal Government Thinkers (MGT), noted in an e-mail interview the Philippines’ power capacity as being “far out from many neighbors in East Asia.”

Citing data from the Central Intelligence Agency’s World Factbook, Mr. Oplas said the Philippines, which has a population of at least 100 million, has a lower power capacity per person compared to neighboring countries such as those of Vietnam, Malaysia, and Laos at 2.1 times, 4.9 times, and 4.9 times, respectively.

LACK OF POWER PLANTS, DE-RATINGS Industry players and analysts said this scenario could have been avoided had there been more power plants available to compensate for those undergoing unscheduled shutdowns or maintenance.

Data from the Department of Energy (DoE) showed there are 126 power plants in Luzon grid alone as of end-2018 with installed and dependable capacities of 16,133.06 MW and 14,641.76 MW, respectively.

However, results of a study from the Energy Regulatory Commission (ERC) released in May showed that up to 72% of these power plants are at least 16 years or older, which may have contributed to the grid’s power deficiency this year.

“Older plants require more frequent maintenance and repairs and may be more prone to unscheduled outages,” Lawrence S. Fernandez, Manila Electric Co. (Meralco) vice-president and head of Utility Economics, said in an e-mail interview.

DoE Undersecretary Felix William B. Fuentebella said in a separate e-mail interview that the occurrence of unplanned and forced outages were considered in the DoE’s assessment of the 2019 summer supply and demand outlook as well as the potential impact of El Niño.

“However, the simultaneous breakdowns were not expected in spite of the preparation and availability of the interruptible load program during the red alert statuses, which resulted in manual load drops,” Mr. Fuentebella said, adding that the delays in the entry of committed power plants “contributed to the limited capacities” in the Luzon grid.

Meralco’s Mr. Fernandez said they have noticed the demand for power has been growing faster in the rest of Luzon compared to the Meralco service area.

“However, it was really the unplanned and forced power plant outages and the delayed entry of new generation capacity that caused the alerts this year,” he said. “This thinning power supply, paired with rising power demand, combine to create a less than ideal power situation.”

“I think the unforeseen factor there was the ‘old plants’ factor; just many of them went on unscheduled shutdowns,” MGT’s Mr. Oplas said.

A closer look at available data showed plants currently online include those built way back in the 1940s and 1950s — plants whose efficiency has eroded through the years.

Two of these plants are located in Luzon — the Caliraya dam-type hydroelectric power plant (HEPP) and the Botocon run-of-river type HEPP, both located in Lumban, Laguna. These plants were commissioned in the early to mid-1940s.

Adding to the forced and unforced outages, the lack of supply is also attributed to plant de-ratings, which happens when a power plant is operating at less than its maximum capability in order to prolong its life.

“The current situation of our power plants and the continuously rising demand suggest that it would be beneficial to our grid if new capacities are built so more supply and reserves are available,” said Meralco’s Mr. Fernandez.

For MGT’s Mr. Oplas, the lack of new peaking power plants being built is also a concern. These are power plants that are generally run when there is high demand or only during peak times.

The economist explained there is little to no incentive in putting up these peaking plants as they can only sell through the Wholesale Electricity Spot Market (WESM), which has installed price caps to protect consumers from excessive price spikes.

“There should be incentives for developers of peaking plants that may be idle for nine to ten months per year, then running only for a few hours per day on hot months… Even if they charge high, say five to ten times the average WESM clearing price on certain hours, it’s still cheaper compared to having massive blackouts, or the poor buying candles (and have more fires) or the middle class and rich buying more generator sets (and have more air, noise pollution),” he said.

“When demand is high during hot months, baseload and mid-merit plants cannot deliver extra,” he explained.

Joe R. Zaldarriaga, Meralco assistant vice-president and public information office head, said the government and power plant operators should look into the causes behind these power plant outages and address them accordingly.

“It would be best to explore ways of better operating, maintaining and sustaining the various power plants and keep them running efficiently. The government should also continue identifying projects of national significance, like large power plants and transmission facilities, and help fast-track their construction and operations,” he said in an e-mail.

DELAY IN POWER SUPPLY DEALS According to DoE’s Mr. Fuentebella, common hurdles faced by proponents in pursuing new power projects include “licensing/permitting challenges” as well as access to financial packages.

For his part, MGT’s Mr. Oplas noted the “thick, wide bureaucracies” in the local and national levels when applying for a power plant project.

“[T]he whole thing would require 359 government signatures, involving 74 agencies and bureaus, covering 43 different licenses and contracts,” Mr. Oplas explained, citing a September 2018 PowerPoint presentation of Senator Sherwin T. Gatchalian, who chaired the Senate’s energy committee in the 17 th Congress.

Meralco’s Mr. Zaldarriaga said for power projects, long-term planning is crucial as the construction of a power plant, which includes the permitting process takes more than five years to achieve.

Business groups have been calling for the construction of power plants to ensure ample long-term supply of electricity. However, hampering efforts is the delay in the approval of power supply agreements (PSA), which is a bilateral agreement between a generation company and a distribution utility for the purchase and supply of power.

A PSA is typically a critical milestone for power projects as these are signed before construction of a power plant starts to reassure banks that the plant will have ready buyers for its output.

The Supreme Court (SC) ruled last month that all PSAs submitted by distribution utilities to the ERC on or after June 30, 2015, must undergo what is called a competitive selection process (CSP).

CSP requires contracts between power generation companies and distribution utilities to be subjected to price challengers, a process that is aimed at lowering electricity cost.

The decision affected seven PSA applications that were filed by Meralco that covered 3,551 MW. The contracts were signed on April 29, 2016, a day before the April 30, 2016 extended deadline set by the ERC.

The ERC promulgated CSP in November 2015 but had to restate its effectivity date to April 30, 2016 through a resolution issued in March 2016. It said the move was prompted by letter-inquiries from distribution utilities and generation companies assailing the legal implication of the CSP to existing power supply deals.

Meralco’s PSAs are with two subsidiaries of its unit Meralco Powergen Corp., which is constructing power plants under subsidiaries Atimonan One Energy, Inc., San Buenaventura Ltd. Co., and Redondo Peninsula Energy, Inc.

The Atimonan project, whose PSA was filed in 2016, consists of two ultra supercritical coal-fired power plants with a capacity of 600 MW each. It was originally expected to be completed by 2021, but has since faced several regulatory issues. The company now looks to complete the project by the fourth quarter of 2025.

Meralco also has a PSA with St. Raphael Power Generation Corp., its joint venture with Consunji-led Semirara Mining and Power Corp. Meralco is also seeking approval for PSAs with Central Luzon Premiere Power Corp., Mariveles Power Generation Corp., Panay Energy Development Corp., and Global Luzon Energy Development Corp.

The high court ruling is viewed as a mixed bag, according to the sources interviewed by BusinessWorld .

DoE’s Mr. Fuentebella said the ruling is a welcome development in the power industry.

“While ensuring transparency, competitiveness, and reasonableness of the power supply cost, it will provide an opportunity to enhance the power supply agreements between the generation companies and distribution utilities that will eventually redound to the benefits of the electricity consuming public,” Mr. Fuentebella said.

For MGT’s Mr. Oplas, it is more of a net negative as this will further delay the construction of power plants.

“It is now 2019 and [the] SC wants to backtrack CSP ruling to PSAs made four years ago? ERC and SC should focus on enforcing CSP only to new PSAs,” the economist said.

Nevertheless, Meralco has said that they will respect the SC’s decision.

“Meralco respects, honors and abides by the SC ruling on [the CSP]. Moving forward, we will conduct CSP to ensure availability of quality, stable and cost-competitive supply in the country,” Mr. Zaldarriaga said.

“Meralco PowerGen, through its subsidiaries, will also work with all the concerned parties and agencies to ensure that planned power plants progress and to have these up and running as soon as possible,” he added.

So far, there are 19 private sector-initiated power plant projects in Luzon targeted to go online between this year and 2023, data from the Energy department as of end-2018 showed. These facilities are expected to have a combined committed capacity of 4,774.8 MW.

Meralco’s controlling stakeholder, Beacon Electric Asset Holdings, Inc., is partly owned by PLDT, Inc. Hastings Holdings, Inc., a unit of PLDT Beneficial Trust Fund subsidiary MediaQuest Holdings, Inc., has interest in BusinessWorld through the Philippine Star Group, which it controls.

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IvyPanda . (2021) 'Power Backups as a Solution to Outage Problem'. 22 January.

IvyPanda . 2021. "Power Backups as a Solution to Outage Problem." January 22, 2021. https://ivypanda.com/essays/power-backups-as-a-solution-to-outage-problem/.

1. IvyPanda . "Power Backups as a Solution to Outage Problem." January 22, 2021. https://ivypanda.com/essays/power-backups-as-a-solution-to-outage-problem/.

Bibliography

IvyPanda . "Power Backups as a Solution to Outage Problem." January 22, 2021. https://ivypanda.com/essays/power-backups-as-a-solution-to-outage-problem/.

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17 Aug 2024 | 05:52 PM UTC

Lebanon: nationwide power outage reported as state power provider announces depletion of fuel oil reserves aug. 17, state provider shuts down last operating power plant in lebanon, causing nationwide outage aug. 17; transport, business disruptions likely..

Lebanon is experiencing a nationwide power outage after state power provider Electricite du Liban (EDL) was forced to shut down its last operational unit at the Zahrani power plant due to a complete depletion of fuel oil reserves on Aug. 17.

The blackout is affecting critical infrastructure across the country, including ports, water pumping stations, sewage systems, prisons, and Beirut-Rafic Hariri International Airport (BEY); disruptions to airport operations and flights, including delays and cancellations, are possible at BEY until power is restored. EDL has said that power restoration will be gradual and dependent on the replenishment of fuel supplies. Lebanese authorities estimated that, as of Aug. 17, power would be restored within the next 24-48 hours.

The South Lebanon Water Establishment has said that the power outage has significantly impacted its ability to pump adequate water supplies. Authorities have urged members of the public to take immediate measures to conserve water and limit water consumption until further notice.

Traffic disruptions and longer driving times are possible during the power outage due to malfunctioning traffic signals. The power outage will likely result in the temporary unavailability of essential services, such as ATMs and filling stations, as well as other business disruptions. Blackouts could adversely affect security protocols, including alarm systems and electronic fences; the incidence of opportunistic criminal activity and vandalism could increase during the electricity outage. Should authorities fail to restore power quickly, demonstrations cannot be ruled out across Lebanon, particularly near government buildings. Authorities will likely deploy a heightened security presence to the sites of any protests that materialize and may engage in clashes with demonstrators, especially if they refuse any orders to disperse.

Consider developing or reviewing business continuity plans (BCPs) vis-a-vis utility outages. Identify business-critical functions that require a power supply. Consider investing in generators and, if applicable, uninterruptible power supply (UPS) units. Charge laptops, tablets, mobile phones, and other business- or travel-critical appliances whenever possible. Consult official sources covering planned or unplanned power outages and monitor announcements from EDL. Confirm flight status if scheduled to travel via BEY, and consider making alternative arrangements for time-sensitive travel as necessary.

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Power Outage essay

PowerOutage

Poweroutages are not strange in Kenya, an African nation which is locatedon the horn of Africa. The country has a population of over 40million residents and according to a report by the World Bank only 23% of Kenyan households have access to electricity [ CITATION APT16 l 1033 ].However, on Tuesday morning the nation woke up to a massive poweroutage that lasted for four hours after a monkey tripped on atransformer. This incident caused one of the largest power outages inthe country as the country’s largest hydroelectric power generatingpower station came to a halt. LastTuesday, Gitaru power station located at the heart of the nation hada power outage that lasted for hours bringing businesses that lack abackup system to a screeching halt. In this essay, the author willdescribe the outage, the duration of the outage, research on theGitaru power station and determine the impact of the outage.

Kenyancitizens recently experienced a historic power outage this week asclose to 5 million businesses and households experienced a poweroutage that lasted for hours. The power outage was accidental as itis believed to have been triggered by a vervet monkey. According toKenGen, Kenya Electricity Generation Company, the body responsiblefor generating over 80% of the country’s electricity the monkeysurvived the ordeal and was handed to Kenya Wildlife Services. Themonkey is said to have fallen on one of the transformers and trippedit causing an overload from the other transformers and hence causinga power outage. This incident caused a loss of 180 MW that isgenerated from the power station which serves over 10% of thecountry’s population hence explaining the nationwide blackoutexperienced on Tuesday morning [ CITATION Gua16 l 1033 ].Although most news sources describe the outage as lasting for onlyfour hours, most Kenyan households spent more than 24 hours in thedark.

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TheGitaru hydroelectric power station is one the recent electricgenerating power plants setup in the country. According to KenGen,the hydroelectric power station is the largest in East Africa as itgenerates over 225 MW from the three units installed at the station.In addition, the plant is crucial to the nation as it supplies atenth of the country’s electricity on the national grid [ CITATION Ken16 l 1033 ].The 180 MW power lossthat lasted for almost one day meant that the facility lost 80% ofthe power generated on that day. Therefore, the 180 MW loss of powerdue to a power outage can be estimated to be 0.22% of the annualpower generated by the plant. This would translate to over $ 1.08Million lost as result of the outage. The assumption is that the costof a kilowatt of electricity generated costs $6. By utilizing theinformation from the Gitaru hydroelectric power plant, it could beestimated that an unplanned 7 day outage might cost the facility over1,575 MW of electricity. This would mean that kenGen would write offlosses amounting to almost $ 9.5 Million in just over a week. This isonly the losses caused by the power outage not to mention other coststhat would be affected as a result of the power outage. As a result,the Kenyan government is seeking to reduce its reliance onhydro-electric power plants as it is investing in renewable energysources.

AP, T., &amp Cook, L. (2016, June 11). Monkey causes nationwide blackout in Kenya . Retrieved June 8, 2016, from CNN: http://www.cnn.com/2016/06/08/africa/kenya-monkey-power-outage-trnd/index.html

Guarino, B. (2016, June 8). Monkey stumbles into hydroelectric power plant and triggers 4-hour blackout across Kenya . Retrieved June 11, 2016, from The Washington Post: https://www.washingtonpost.com/news/morning-mix/wp/2016/06/08/monkey-stumbles-into-hydroelectric-power-plant-and-triggers-4-hour-blackout-across-kenya/

KenGen. (2016, June 11). Hydro Power Stations . Retrieved June 11, 2016, from KenGen: http://www.kengen.co.ke/?q=content/hydro-power-stations