Geographic distribution of power outages
across the continental U.S. during heat wave events, including both standalone
heat waves and those compounded with other weather events. Areas not associated
with heat wave-related outages are shown in light gray. Credit: Scientific Reports (2025). DOI: 10.1038/s41598-025-15065-x
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frequent and intense weather phenomena like heat waves, windstorms, or
atmospheric rivers often come in pairs and these challenging combinations
stress the power grid and lead to outages. A multi-year analysis is the first
of its kind to analyze combined weather events and county-level outage data
across the United States.
The research was published in Scientific Reports and was led by researchers from UConn's Outage
Prediction Modeling (OPM) team, including Environmental Engineering Program
Ph.D. student Shah Saki, Board of Trustees Distinguished Professor and director
of the Institute of Environment and Energy, Emmanouil Anagnostou, assistant
research professor Giulia Sofia, and Bandana Kar, researcher at the National
Laboratory of the Rockies.
When it comes to strain on the grid,
heat is a big factor, explains Saki.
"While heat has long been
recognized as a stressor on power systems, the new analysis shows its effects
intensifying and interacting with other weather hazards," says Saki.
The study examines how heat waves impact
power outages in different regions across the contiguous United States. The
regional nuances are important; for instance, if the outage is compounded by
other weather phenomena like thunderstorms, high wind, or intense
precipitation, which may be more frequent in some areas compared to others.
These extreme weather events also tend to follow high heat days, Saki explains,
and researchers realized they could not look at heat waves alone, but that the
research would be more impactful if they analyzed the data from a multi-hazard
standpoint.
"A tricky aspect of research like
this is that utilities usually do not share outage information upfront with the
customers or researchers," says Saki, "and access requires extra
permissions."
Anagnostou explains, "However,
thanks to a Department of Energy (DOE) and Oak Ridge National Lab program
called DOE Eagle-I system, we now have access to outage records from 2015 to
2022, which made this analysis possible."
The approach was also novel in that it
did not focus on a single region; rather, the scope included the eight
Independent Service Operator (ISO) authority regions across the country. For
the sake of the analysis, Saki explains that some of the ISOs were combined.
The researchers combined this outage
data with county-level weather data, where they made assumptions about the
start and endpoints for each outage, and also the primary cause.
To address this, the researchers matched
outage timing with National Weather Service (NWS) alerts, allowing them to identify the most
likely contributing weather conditions. All of these data were used to make a
self-organizing map via deep machine learning.
"We try to see if there is a
compounded effect by heat waves, and at the same time the outage is happening,
how do we determine the main driving factors causing these outages?" says
Sofia. "Is it wind, or rain, or just the heat alone? The two major things
we looked at were what factors are causing the most frequent or most damaging
outages?"
Saki explains that the machine learning
algorithm looks for similarity within the data to create clusters; in this
case, clusters of regions impacted by the same weather variables. Fortunately,
the process is automated and unsupervised, and the clusters reveal trends and
patterns about the outages that may otherwise be overlooked.
"That's
one of the biggest advantages of using clusters to identify which of the
weather phenomena and the outages are alike, and based on that, we can consider
which was the most damaging and impactful weather phenomenon associated with
that cluster," says Saki.
The
results show the importance of considering the nuances between heat
wave-related power outages in different regions, says Anagnostou. For example,
in California heat is oftentimes compounded by high wind events. In Texas, heat
waves are frequently followed by periods of intense rain. These compounding
events stretch the grid beyond normal operating limits, and result in outages.
Most
outages were short, says Saki, but that was not always the case.
"The
50 percentile is about five hours, so the recovery time is quick, but the
maximum is around 358 hours, or 14 days," he says. "It was surprising
to me that these compounding events can cause that long of an outage."
One
notable example of compounding effects was Hurricane Laura, which was preceded
by a multi-day heat wave in August of 2020.
"When
we have compounding effects, as in the case of Hurricane Laura, those outages
were long," says Saki. "This also happened with some heat waves which
caused wildfires in some part of the California. Those are the major findings
which we found in the paper."
Saki
says he expected to see more outages in regions like Florida, but that was not
the case. This may be due to programs that have been implemented to increase
grid resilience, which is a testament to the importance of research and
proactive efforts to build energy resilience.
"Long-term
investments in grid hardening can
meaningfully reduce outage risk, even as extreme heat increases," says
Saki.
The
findings underscore that regionally tuned resilience planning outperforms
national one-size-fits-all approaches, as power grids fail for different
reasons depending on local climate and weather patterns.
"Power
outages are closely tied to regional climatic behavior," says Anagnostou.
"This kind of analysis helps policymakers and regulatory bodies better
understand whether their region is more vulnerable to extreme heat alone or to
compounding weather events."
The
findings have already garnered attention from policy makers and media outlets
who see the impact the findings can have in preparing for the future. Saki's
ongoing Ph.D. research is examining the causes of damage to the grid because
that information can help inform future projects to harden the energy system.
"If we move to take this data to the next step into the future climate, how that's going to impact the future scenarios, because the policymakers are interested to know the impacts now, and how that's going to impact in the future," he says.
Provided by University of Connecticut
Source: Building energy resilience by understanding nuances of power outages across the US
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