Climate Resilience Analysis

This interactive storyboard summarizes findings from recent Climate Vulnerability Assessments (CVAs) conducted at nuclear power plants under EPRI and INPO guidance. CVAs are systematic, forward-looking evaluations of how projected climate hazards — including extreme heat, drought, intense storms, and biological fouling — may affect plant structures, systems, and components (SSCs) and their ability to operate reliably. The storyboard walks through the CVA process in four phases: recognizing climate risks and assembling cross-functional teams; screening and characterizing site-specific climate hazards; evaluating plant-level exposure and vulnerability through engineering analysis and walkdowns; and prioritizing response actions using an eliminate–mitigate–accept framework. Key findings indicate that rising air and cooling water temperatures represent the dominant hazard across all sites assessed, that the majority of SSCs retain adequate design margin under current conditions while a small number of cooling and heat-rejection systems show narrowing margins under mid-century projections, and that indirect and cascading exposure pathways — rather than direct thermal stress on individual components — often drive the most consequential vulnerabilities. Lessons learned emphasize the value of cross-functional engagement, system-level exposure assessment, structured walkdowns, coordinated multi-site campaigns that share insights in real time, and early initiation of design-basis data requests.

Access the Story Map here: Climate Vulnerability Assessment

Electric utilities face challenges from tree related outages, which remain one of the most significant drivers of service interruptions across distribution systems. These outages already impose high reliability and resilience costs today, and the combination of aging infrastructure, evolving vegetation conditions, and intensifying climate stressors is expected to increase this risk in many regions. Vegetation management is one of the most resource intensive and operationally complex tools available for reducing outage risk, yet its effectiveness varies widely across geographies, forest types, weather regimes, and utility practices. Given the scale of investment required, utilities need a clear and evidence-based understanding of how vegetation management affects outage rates under current conditions, how these effects may change as the climate evolves, and how vegetation management compares to or interacts with other adaptation strategies. This report provides a foundation for understanding tree failures, their interactions with overhead distribution electric infrastructure, and the factors that influence how vegetation management can help reduce outages during storms, both today and in a changing climate moving forward.

Gridded reanalysis products are widely used in energy system planning and operations to characterize long-term weather and extreme events. This study evaluates how three widely-used reanalysis products (ERA5, ERA5-Land, and MERRA2) capture the magnitude, timing, and shape of daily temperature cycles across the contiguous United States compared to in-situ station observations from 2000–2022. Results show that while bias correction can reduce some of the bias in gridded temperatures, discrepancies in the timing and shape of daily temperature extrema often remain. For example, ERA5, exhibits a 1–2 hour lag in the occurrence of daily extrema, most pronounced in winter and for western mountainous regions. While ERA5 generally shows the closest agreement with station observations in capturing the shape of hourly temperature around extrema, ERA5-Land and MERRA2 match observations more closely at many locations. These timing and shape discrepancies have direct implications for load forecasting, peak demand estimation, and grid flexibility requirements. We recommend that energy system practitioners carefully validate reanalysis datasets using metrics specific to their applications and regions before integration into planning and operational models.

Recent extreme temperature events have challenged the energy grid, prompting new regulatory standards for grid resilience. However, the complex, non-linear relationship between weather and grid performance is often obscured by critical data gaps, thus planning for higher-intensity events without addressing these shortcomings can create a false sense of security. This technical brief summarizes a survey of the EPRI Global Change, Climate Risk, and Target Setting research advisors, which identifies a pressing practitioner need for technical guidance. It further details current data limitations, discusses several key implications of recent North American Electric Reliability Corporation (NERC) standards, and proposes robust extreme temperature event definitions to strengthen system planning.

In response to the U.S. Department of Energy’s (DOE’s) draft report, A Critical Review of Impacts of Greenhouse Gas Emissions on the U.S. Climate, released in July 2025, EPRI submitted formal comments during the public review period. As an independent, non-profit research organization with a public-benefit mission, EPRI often develops objective, science-based comments grounded in its extensive R&D portfolio and its unique role as the electricity sector’s collaborative research organization.

EPRI’s comments in this case focus on the implications of the DOE report for the power sector, particularly in the areas of reliability, resilience, and adaptation. Drawing on research from EPRI’s Climate REsilience and ADaptation initiative (READi), as well as longstanding work in low-carbon pathways, air quality, and the social cost of carbon, the comments emphasize the importance of high-quality data, robust scientific foundations, and transparent methodologies. The report examines the DOE’s treatment of extreme weather, emissions policy, and socioeconomic risks, and offers constructive recommendations to improve the scientific rigor and practical relevance of the final report. EPRI’s contributions aim to support informed decision-making and continued public and scientific engagement on climate resilience and energy system planning.

The increase in climate risk disclosure requirements has led to a proliferation of third-party physical climate risk assessment frameworks. It is difficult, however, to readily comprehend their strengths and weaknesses. As a result, utilities have expressed a desire to better understand the capabilities and differences between frameworks. Researchers in EPRI’s Global Change, Climate Risk and Target Setting research group (Project Set 201E) proposed an initial characterization template to describe and summarize framework capabilities for electricity, gas, and transmission and distribution utility applications. The characterization template is a spreadsheet with a series of questions that elucidates a framework’s basic functionality, including types of assessment supported, scientific underpinnings, assumptions, and uncertainty characterization. The goals of the characterization template are to provide utilities with a standardized approach to facilitate the following: (i) understanding and comparing framework capabilities; (ii) assessing framework capability for supporting utility applications; and (iii) informing utility framework conversations with providers and stakeholders. The accompanying characterization template spreadsheet also provides an example set of responses for the First Street Foundation’s framework, which includes their Flood Model, Fire Model, Wind Model and Correlated Risk Model. The initial characterization approach is offered for review and refinement with the goal of applying it to additional frameworks and developing a capability assessment library resource.

Companies are increasingly tasked with incorporating climate change information into planning and modeling. Availability of climate data is not the biggest challenge, as there is an abundance of public and proprietary climate data tools and portals, with more being added. However, understanding the information and how best to use and interpret it for local assessments is technically challenging, time consuming, and often expensive. For this reason, assessing local climate is not trivial, and creating actionable insights even more difficult.

This document assesses the limitations of climate data available as of late 2024 for electricity sector planning and operations. Climate READi acknowledges that research and data development is rapidly evolving in this space. We hope that this resource, informed by EPRI’s expertise in power system applications, can help focus these activities on high value data development and may consider updating it periodically as work advances.

This report is structured as an outline to systematically assess data gaps by product type (e.g., weather and climate observations, climate model simulations) and details data gaps specific to key climate variables and hazards. In addition, this assessment discusses next steps and considerations for addressing climate data gaps. Key takeaways from this assessment include:

• Observational data gaps of climate variables such as solar irradiance and hub-height wind speeds exist due both to the small volume of historical measurements and to the lack of public access to the proprietary measurements that do exist.
• Data gaps of climate model simulations of variables at spatial (e.g., local) scales are mostly driven by technical and re­source constraints, such as the ability to accurately represent complex local topography, computing speed, and storage space. Similar constraints are often cited regarding provision of relevant temporal (e.g., hourly) data, but are no longer limiting factors in this case. Rather, misalignment between the climate modeling and power sector communities around data use cases and reconciling what data are needed with what data are possible are predominantly driving temporal gaps.
• Observational data on severe weather such as thunderstorms, tornadoes, hail, ice storms, and local scale extreme wind events that are highly impactful to the power system, are limited by the sparse sensor network and its short history. Climate model data for these phenomena are limited by their relatively coarse spatial and temporal resolution. Many extreme weather events can only be resolved by high-resolution weather forecast models. Further, even with unlimited computational resources, these models are still limited in their ability to accurately represent important environmental process, especially at small scales, and become increasingly difficult to validate at fine scales due to a lack of observational data for validation. Lastly, weather forecast models cannot yet be run out for many decades into the future, making for­ward-looking information on individual events difficult to produce. However, climate projections of conditions associated with severe weather can provide some understanding of changing risks.
• Efforts to improve climate literacy in the power sector are valuable to allow those utilizing climate data in downstream power system modeling and analysis tasks to better understand available climate data and potential data applications.
• Collaborations between climate data providers and power system modelers and planners are ongoing and needed to en­sure key data needs are addressed and data are provided in a usable format.
• Notwithstanding the former two bullets, it must be understood that climate data comes from a diverse range of observa­tional and modeling platforms many of which are highly complex. Understanding characteristics like bias and uncertainty of data from different sources across different types of weather and/or electric system conditions is crucial. It is important to consider these factors within the context of specific use cases. For example, resource adequacy assessment requires a good understanding of the data in the tails of weather variable distributions. Organizations seeking to assess climate risks should proactively engage relevant climate specialists rather than simply taking data/tools off the shelf and relying on a non-specialist to analyze them.

Hurricanes, or more generally tropical cyclones, are known to cause extensive damage to electric power system infrastructure, as high winds and heavy precipitation often leave felled trees and downed power lines in their aftermath. This can result in long-duration power outages following a storm, as utility crews work to repair damaged poles and lines as quickly as possible. There is a growing body of research focused on how climate change will affect future storm characteristics in terms of frequency, intensity, and location. While studying the change in hurricane behavior itself is the first step, the motivation for this case study lies in gaining a better and more nuanced understanding of what a change in storm characteristics might mean for power system impacts. Namely, how might climate change affect the risk of hurricane-induced power outages?

As an initial demonstration resulting from a collaboration between EPRI and PNNL, we’ve coupled synthetic storm tracks, created under both current and future climate conditions, with a prediction of power outages resulting from each storm to characterize broad trends at the county scale across U.S. Gulf and Atlantic coast states. Explore the linked story map to see how outage events – looking at different measures of frequency and magnitude – are projected to change in a future climate. Each layer offers a different picture of risk and can be used to conceptualize a community’s lived experience, inform a utility company’s planning decisions, or bound expectations for increasing risk. This map provides a way to dive into these results at the county level, showing several different metrics of interest:

• The number of hurricanes (i.e., exposure to hurricane-force winds) occurring per decade, with a map layer showing simulated values for the current climate, the projected values for the future climate, and the change between the two
• The number of outage events experienced per person per decade, with a map layer showing simulated values for the current climate, the projected values for the future climate, and the change between the two
• The number of severe outage events per decade (here defined as events with at least 50% of the county population without power), with a map layer showing simulated values for the current climate, the projected values for the future climate, and the change between the two
• The 20-year return period outage magnitude (here defined as the percentage of population without power), with a map layer showing simulated values for the current climate, the projected values for the future climate, and the change between the two

To access the story map click here: Climate READi (epri.com)

Wildfires threaten electric companies’ ability to provide reliable and affordable electricity to the customers and communities they serve. Wildfires, regardless of ignition source, present a significant threat to electric infrastructure and public safety. In order to mitigate these threats, electric companies continue to play a pivotal role in raising awareness of and investing in solutions. With climate change and the emergence of increased extreme weather events, the power delivery systems of the future must be more prepared for even more wildfire threats and other weather-related dangers.

The current landscape of wildfire data, models, tools, and services is complex and challenging to navigate for decision-makers. This raises the need for an objective evaluation of wildfire data products to assist in selecting the most suitable option for specific objectives. This research reviews 36 different wildfire risk products and 13 wildfire smoke products. The products are evaluated according to a set of evaluation criteria. For wildfire risk products, these evaluation criteria are spatial extent, product purpose, product type, spatial resolution, temporal extent, temporal resolution, risk dimensions, product complexity, and accessibility. Wildfire products that only offer real time wildfire maps are not evaluated. For the wildfire smoke products, evaluation criteria are spatial extent, product purpose, product type, spatial resolution, temporal extent, temporal resolution, and accessibility.

The discussion section of this report summarizes key findings and identifies wildfire data gaps and limitations. This report is accompanied by an online interactive webpage, including a filtering tool that can be used to identify the most useful product(s) for a specific user need. The purpose is to direct readers towards the optimal products for their specific application and not as an authoritative assessment of the best products overall. This report is not an exhaustive source of all wildfire products, especially proprietary ones. Readers are encouraged to submit products for review, and updates will be made to the web version of this report on an ongoing basis.

To help utilities and operators more effectively evaluate how climate change will impact their business and operations, EPRI’s Climate READi research initiative has developed a six-stage process to collect, analyze, and share climate change information specific to their region. Power system planners, asset operators, and risk management professionals can use this approach to explore the physical climate risks they face now, and to show how these risks may change in the future. The steps include collaborative discussions with stakeholders to launch the process, followed by scoping the nature of the process and the hazards involved, determining the best metrics to measure and show the climate-related impact, analyzing the results, and sharing what has been learned.

To access the Story Map click here: EVALUATING LOCAL CLIMATE CHANGE IMPACTS

The Climate READi Climate Data User Guide is intended to give electrical system planners, engineers, regulators and stakeholders a concise, comprehensive guide to the selection of suitable climate data for physical climate risk assessment. It includes brief reviews of the climate modeling science and statistics used in climate science, as well as specific descriptions of sources of past and future data.

To access Climate Data User Guide v1.0.0, click here: https://apps.epri.com/climate-data-user-guide

Benfits and Values

The User Guide consists of more than a dozen articles with multiple cross-links. Each is intended to be useful on its own, but with only the level of detail needed to cover its own particular topic. It is intended to provide comprehensive guidance for electric power companies on selecting and applying climate data in a diversity of power system applications, to provide a scientifically informed and technically grounded resource for stakeholders interested in understanding suitable uses of climate data in power sector applications, and to address persistent questions from the electric power sector on the use of climate data in system planning.

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Planning for future climate conditions is critical as the electric power sector continues to face operational and planning challenges from climate-related events such as extreme temperatures, prolonged drought, wildfires, ice storms, flooding, and hurricanes. Impacts from these events include direct physical damage to utility assets; operational challenges when extreme weather events render assets unavailable or lead to reductions in asset efficiency, output, or capacity; and planning challenges when changes in chronic climate conditions or extreme weather alter planning assumptions that form the basis of system design.

Documentation of how different climate variables and climate hazards can impact different components of the electric power system is an important first step in being able to identify and assess potential vulnerabilities to climate change. For three years, EPRI’s Exploring Climate Impacts in Utility Operations and Planning Interest Group (ECI IG) has focused on systematically characterizing the potential impacts of climate change (“climate impact pathways”) across the entire electricity system, from generation to the grid to the customer, which led to the development of a “Library of potential types of climate-related impacts and response options” for the electric power system. In 2023, the scope of the ECI IG expanded to include climate impacts to sectors adjacent to the electric power sector. Insights for impacts to roads and rail system, the gas-electric interface, and telecommunication infrastructure are included in the 2024 version of this document.

Drawing on in-house expertise in climate analysis, engineering studies, and power system modeling, EPRI convened an expert forum where participants could: (1) evaluate the scientific understanding of changes in climate conditions and extreme weather events that affect the electric power system, (2) characterize potential impacts of these climate variables on various components of the electricity system or adjacent sectors, and (3) identify an initial set of potential response options. This encyclopedic resource summarizes discussions and insights from the ECI IG and served as a foundational input for EPRI’s Climate Resilience and Adaptation Initiative (Climate READi). Efforts are ongoing in Climate READi to further understand climate impacts to and adaptation strategies for power sector assets.

The Climate Data Inventory is an online resource for discovering and understanding climate data that are available to support power system analyses. It catalogues a list of climate datasets and provides a searchable database with multiple filters, dataset details, and documentation. While the inventory represents a curated list for potential use in power system applications, it is not intended to be comprehensive list of every available climate dataset and excludes hyper-local and proprietary datasets.

The Climate Data Inventory should be used in conjunction with other Climate READi Workstream 1 resources, including the Climate Data User Guide, which provides guidance on the selection and application of climate data in various power system analysis contexts.

To access click here: Climate Data Inventory (epri.com)

Global climate models (GCMs) are an important tool for projecting future climate conditions under various greenhouse gas emissions scenarios. Although they are of key use for planners, their size and complexity often make them evaluate the climate at coarse spatial scales (generally around 100 km) and temporal scales (generally daily), whereas most weather and climate impact assessments require much more localized and granular information. Because of this, scientists and practitioners often convert the coarse data into finer scale through a set of methods called downscaling. This READi Insight briefly summarizes the main forms of downscaling—statistical, dynamical, and machine learning methods—and highlighting their relative advantages and disadvantages.

The electric power system is a physical system that is exposed to numerous climate-related hazards. It relies increasingly on weather-dependent resources that need weather and climate data to assess electric supply availability. Because of this, the electric power sector must anticipate and adapt to a range of climate conditions and system responses, both current and future, under which it will operate.

Climate-informed decision making requires understanding the constituent components of physical climate risk, so this training aims to help electric power system asset managers, engineers, operators, and planners understand those components. EPRI has designed this training to assist in the implementation of physical climate hazard, exposure, and vulnerability assessments within electric companies or wider electric power systems.

Climate READi’s Climate 101 training series, organized as a series of webcasts or recorded videos, aims to facilitate actionable conversations between climate data providers and power system analysts. Climate Hazard, Exposure, and Vulnerability Assessment 101, the second training in the series, broadly covers the issues of hazard, exposure, and vulnerability as applied to climate risk and resilience, with three modules covering these respective components. Extra attention is given to real-life examples and case studies.

Climate Hazard, Exposure, and Vulnerability Assessment 101 is a resource for building climate literacy across the electric power industry and is a tool for level setting key concepts and terminology among climate experts and other subject matter experts. It provides access to high quality, technically rigorous training that is designed to facilitate more productive and collaborative future conversations between members of a company’s physical climate risk assessment team.

The initial training in the series, "Climate 101: Physical Climate Data," along with accompanying recordings, is available here.

To access the training recordings for this training series, click the links below and choose the "Attachments" tab:

• Module 4
• Module 5
• Module 6

Evaluating the operational and business risks to the power system of a changing climate is relatively new for many utilities and operators, and there is increasing stakeholder interest in having companies disclose physical climate risks. Developing the data needed to assess if and how the climate has or could be changing is essential for being able to evaluate whether there are climate risks that need to be addressed. However, companies have unique resources, systems, customers, and risk perspectives, thus the data developed must be tailored to their needs. This document presents a step-by-step data development process and illustrative analysis for developing localized climate change information specifically to inform power system asset operators, planners, and risk management. The illustrative analysis walks through a process of five steps, from site selection through to alternative data communications, that is initiated by a facilitated requirements discussion with internal stakeholders. Each step has its own discussion, inputs, and outputs that together build the information and dialogue foundations needed for subsequent steps. The illustrative analysis consists of actual historical and projected local physical climate change data development and assessment for five specific locations across the United States. A diverse set of locations was chosen with project participants to facilitate exploration of capabilities and challenges for a diversity of hazards. Figures and tables are created for each location and hazard to illustrate different types of results and to demonstrate how these results may be communicated in different ways for different internal and external audiences. The illustrative nature of this document makes it generalizable and lays the groundwork for companies looking to conduct local climate risk assessments. The work presented here also serves as a case study for EPRI's Climate Resilience and Adaptation Initiative (Climate READi), with relevant insights incorporated into Climate READi guidance documents, such as the Climate Data User's Guide.

Traditional approaches to power system planning often rely on historical weather data to model electricity generation and demand, but this approach will leave systems vulnerable to climate change as local weather patterns have changed and will continue to change in the future. Rising temperatures will, on average, increase load while simultaneously derating power lines. Changes to other weather variables may impact power systems as well. Low winds contribute to line derating and reduce wind power, while drought challenges thermal generator cooling and hydropower resources. To build climate-resilient systems, it is crucial to integrate forward-looking climate data into models for system planning. This remains a substantial challenge because current Global Climate Models (GCMs) generally output daily data, while system planners need hourly data to capture rapid weather fluctuations that impact generation and load. These diurnal fluctuations are important to capture since operational decisions are commonly made on an hourly or even sub-hourly basis. This Quick Insight outlines different techniques for generating future hourly time series data and discusses challenges in projecting future weather extremes.

The National Weather Service declared in early June of this year that El Niño has emerged over the tropical Pacific Ocean, and there will be a 56% chance that it will develop into a strong El Niño condition in the late fall of 2023 through spring of 2024. In early July, the World Meteorological Organization (WMO) also declared the onset of El Niño conditions. The warmer-than-average ocean temperatures of El Niño, together with the global warming conditions have led to the record-breaking global mean temperature observed in July 2023 and numerous other all-time high temperature records in cities across the globe.

In the face of climate change, the electric power system is experiencing a renewed focus on resilience and adaptation to physical climate risk. Resilience—defined as the ability to anticipate, respond to, and recover from potentially disruptive events—differs from power system reliability by explicitly including extreme events that are sufficiently rare, cause multiple concurrent failures, affect a wide area or large number of customers, and require more complex restoration strategies. Extremes are thus a primary focus of climate-re­lated resilience since changes in extreme events are likely to be more impactful to the power system than changes in average conditions. This Quick Insight, as part of EPRI’s larger Climate 101 training series, discusses two definitions of extreme events that may arise from the use of climate data, namely climatological extremes and power system operating extremes.

Climate data cover a wide range of timescales, and each type has its own attributes and applications. When assessing impacts of climate to their systems, electric power system planners, operators, and engineers may need to consider potential exposure and vulnerability across multiple times­cales, so it is important to understand how climate data is realized in each. This Quick Insight, as part of EPRI’s larger Climate 101 training series, introduces the unique attributes and applications of historical data, near-term predictions, and climate model projections, so that power system personnel can correctly identify and contextualize the proper data for climate-related planning and operations.

Extreme weather events and climate change are altering how energy companies think about planning and operations of the power system. The global response to climate change adds another dimension of ongoing change: our energy systems are decarbonizing, bringing a shift toward electrification for many end-use energy demands. As the move toward electrification increases society’s dependence on the power grid for meeting basic needs, the threats of climate change will require increased resilience.

In this report, which brings together a vast array of literature from researchers and industry stakeholders, we address climate risk, power system impacts, and current practices to address power system resilience against climate hazards. We also focus on what new research or guidance is needed to consistently integrate physical climate risk across multiple facets of decision-making within a company. These decisions span planning and operations across generation, transmission, distribution, and markets, and include customer-side considerations such as technology adoption, health impacts, and equity. Recognizing the need to account for costs of inaction and societal benefits associated with greater resilience, we include an overview of approaches for valuing and prioritizing resilience investments in a cost-benefit framework. In addition, we identify the importance of metrics across all of these spaces, as they will be needed to compare and evaluate options to justify adaptation and resilience-focused investments.

Extreme winter weather can pose numerous challenges to power system operations and load forecasting. As the power system transitions towards a low-carbon future, these challenges may evolve. Despite overall global trends of warming, extreme winter weather—which may be characterized by extreme cold, heavy snow, and/or significant ice—is expected to continue to impact power system operations and planning. Increasing electrification rates and the changing resource mix will likely shift the drivers of risk when it comes to extreme winter weather. For example, electricity loads in the winter in some regions are likely to increase as home heating and transportation demands switch from fossil fuels to electricity, potentially adding stress to the power system during extreme winter weather. Systems that were historically summer peaking may transition to winter peaking under high electrification futures, increasing the importance of understanding the full range of winter weather-related operating conditions. These trends provide strong motivation for better understanding and preparedness for current and future winter weather conditions. Additional emphasis may be placed on weather forecasts to anticipate demand and prepare for physical impacts to infrastructure, but adequate preparation depends on the quality of both weather and load forecasts.

The electric power system is a physical system that is exposed to numerous climate-related hazards. It relies increasingly on weather-dependent resources that need weather and climate data to assess electric supply availability. Because of this, the electric power sector must anticipate and adapt to a range of climate conditions and system responses, both current and future, under which it will operate.

There are numerous types of climate data that are available to support climate-informed decision-making, so this training is designed to help electric power system asset managers, engineers, operators, and planners have actionable conversations about the different types of climate data available to them and their suitability for different analysis applications. EPRI has designed this training to be able to facilitate the first of many conversations between climate data providers and power system analysts.

Climate READi’s Climate 101 training series, organized as a series of webcasts or recorded videos, aims to facilitate actionable conversations between climate data providers and power system analysts. Specifically, the first training in the series, Physical Climate Data 101, aims to establish a common knowledge base on types of climate data, climate modeling, and associated terminology. Extra attention is given to state of scientific understanding and uncertainty regarding observed and projected trends in weather and climate events. Physical Climate Data 101 consists of three modules, covering (1) an overview of climate data; (2) climate models, scenarios, and projection data; and (3) trends and understanding of extreme events.

Physical Climate Data 101 is a resource for building climate literacy across the electric power industry and is a tool for level setting key concepts and terminology among climate experts and other subject matter experts. It provides access to high quality, technically rigorous training that is designed to facilitate more productive and collaborative future conversations between members of a company’s physical climate risk assessment team.

To access the training recordings, click the links below and choose the "Attachments" tab:

• Intro and Module 1
• Module 2
• Module 3

To access the course overview guide for Climate 101, click here.

The second training the series, Climate Hazard, Exposure, and Vulnerability Assessment 101 (Climate 101 Modules 4, 5, and 6), released in January 2024 can be found here.

The electric power system is a physical system that is exposed to numerous climate-related hazards. Climate change is expected to present new challenges to the electric sector, for which asset managers and planners must adequately prepare. This document presents an inventory of adaptation investments and resilience practices related to climate extremes and changes for the electric power sector, based on a review of published academic literature and industry reports. Given the wide range of effects from different climate hazards on different components of the power system, this catalog is organized primarily by asset type, with particular applications, timescales, and aspects of risk reduction addressed. Where available, published cost estimates are also included. The resulting inventory may provide utility operators and planners with a reference source for the various climate adaptation options available to them.

In this Quick Insight, Climate READi evaluates the severity of recent extreme heat events in the context of historical records and climate change and potential future implications of extreme heat for the power system.

In this Quick Insight, Climate READi evaluates the severity of recent extreme heat events in the context of historical records and climate change and potential future implications of extreme heat for the power system.

This Technology Innovation Quick Insight examines how extreme weather events impact the ability of supply and demand resources to meet customer electricity demand and how resource adequacy assessments should change to account for changing weather patterns.

Electric utilities are experiencing an increase in the number and intensity of extreme flooding and impacts on operations and physical assets. Most electricity infrastructure is built to withstand past or current flood related hazards. Due to long lifetimes, electricity systems are likely to be exposed more frequently to more extreme flooding than those for which they were designed and may not operate as intended under those conditions. Additionally, investors are increasingly analyzing the physical climate risk of their portfolio of investments. For these reasons and others, electric utilities may be considering their physical climate risk from flooding now and in the future. Federal Emergency Management Agency (FEMA) flood zone maps have been a ‘standard’ flood risk assessment data source, but have been shown to underestimate flood risk by not accounting for current and future environmental changes. Newer open source and proprietary models, tools, and services to assess flood risk have emerged, but how do electric utilities evaluate them?

This research identifies important criteria for evaluating flood risk assessment products, provides an overview of fourteen flood risk products, evaluates the fourteen flood risk products based on the evaluation criteria, and applies a subset of selected products to two case study locations (central Pennsylvania, along the Susquehanna River; and coastal Texas, near Houston) followed by a synthesis and comparison of the results of the case study to industry-standard FEMA flood maps.

Flood risk models can be challenging to understand for those not versed in coastal, fluvial, and pluvial flood modeling. This report provides a review by subject matter experts that can be used as a resource for electric utility staff considering flood models, tools, and services.

To better prepare and plan for potential extreme events, the Los Angeles Department of Water and Power (LADWP) worked with the Electric Power Research Institute (EPRI) to conduct a synthesis climate assessment (SCA). The purpose of the SCA is to assess current and future climate conditions in the Los Angeles region, including extreme weather events, and to identify vulnerabilities relevant to LADWP’s power system.

EPRI also performed a transmission resilience assessment (TRA) for three possible future scenarios of the LADWP system in the year 2030. The team used the risk-based Resilient System Investment Framework (RSIF) to assess the impacts of extreme contingency events and quantify the resilience of the scenarios.

This document presents an analysis on historical and projected changes in windspeed and solar irradiance across the United States. Windspeeds and solar irradiance are expected to change as the climate warms, but the magnitude of these changes are locationally specific and generally small compared to the observed changes from year-to-year. For this reason, increased understanding of interannual variability in wind and solar resources may be a higher priority than long-term changes in wind and solar resources. This document lays the groundwork for future studies to assess the impact of temperature on wind and solar output.

This document presents the current scientific understanding of the relationship between climate change and various types of extreme weather events, including extreme cold, extreme heat, precipitation, droughts, wildfires and coastal flooding. Climate change has occurred, and more is likely, with changes in extreme weather expected. Projected changes in sea levels, extreme heat and cold are much more certain than changes in precipitation, drought and wildfires. However, a warmer climate is not necessarily the primary driver of all these extremes as many factors, such as human influence and natural climate variability, may also contribute to inter-annual and long-term changes. As such, these other factors are also relevant to managing extreme weather risk. This document concludes with EPRI's approach to systematically examining potential climate impacts and responses for utility operations and planning.

This Technology Innovation Quick Insight examines what the polar vortex is, how it affects power system infrastructure, and how utilities might mitigate its effects in the future.

This project advances EPRI modeling capabilities and methods for estimating the potential impact of changes in air temperature on energy demand for space conditioning in the United States.

Specifically, we demonstrate a structural approach within EPRI’s US-REGEN end-use demand module, which projects hourly energy demand from the bottom-up for several key end-use sectors. Electricity demand for heating and cooling is calculated using observed hourly air temperature in a building energy model emulation that projects the evolution of space conditioning technology and building stocks with exogenous assumptions about technological change, fuel prices, and socioeconomic growth. We begin by modifying the model such that the temperature parameter is indexed over time, and the distribution shifts across time periods based on the assumed climate scenario. The reference case assumes no climate change and stationary weather, accounting only for non-climatic factors affecting space conditioning demand in 2050. The baseline scenario is called ‘trend’, which extends the observed annual trend in the 40-year historical MERRA sample for each location (collection of grid cells associated with a particular heating/cooling zone within a model region). Next, we introduce a set of ten CMIP6 scenarios that are quantile-based temperature deltas for each grid cell based on 5 global climate model projections for two CMIP6 scenarios, SSP1-2.6 and SSP3-7.0. For all of these scenarios we run the end-use demand module in order to assess the impacts of higher air temperatures on energy demand across the U.S. Specifically, we develop temperature-adjusted annual load projections for future space conditioning demand under future conditions.

In the reference scenario without warming, we find that annual cooling energy requirement declines steadily between 2015 and 2050, as efficiency improvements in cooling technology and building stock efficiency are projected to far outweigh growth in cooled floorspace. For heating, we find that less final energy is required to meet growing service demand due to structural change and efficiency improvements, though electricity’s share increases relative to other fuels, and this electrification of the heating sector leads to strong growth in total and peak heating loads. The effect of warming works in the opposite direction of both mechanisms (i.e., cooling-efficiency and heating-electrification). For cooling, projected warming under SSP3-7.0 in 2050 negates the expected efficiency gains in terms of annual energy. Under the warmest climate realization, SSP3-7.0 in the UKESM1-0-LL model, residential electricity demand for cooling in 2050 is 30% greater than the baseline trend projection. This is evident across all regions, though the effect is smallest in Florida and Texas, and largest in New England and NE-Central. The potential for electrification of building heating to drive up winter electricity consumption is moderated by all warming scenarios. Moreover, even the baseline trend of warming causes final energy (electric and non-electric) demand to drop by a quarter across the US. Because of the relative size of heating versus cooling energy in most regions (Florida and Texas being exceptions), this avoided heating demand generally outweighs the additional energy for cooling.

This bottom-up approach complements the existing climate impacts literature, as many studies have relied on empirical models that estimate the statistical relationship between weather and electricity use (e.g., see reviews in Dell et al, 2014 and Auffhammer et al, 2017) – our results from a structural basis offer a point of comparison to previous estimates. Furthermore, this project helps to produce temperature-adjusted load projections that can be utilized by the broader community of energy-economy models to better assess the electric system’s vulnerability to and plan for different climate conditions. Ultimately, we will use the US-REGEN capacity expansion and dispatch model to assess these demand-side impacts on the electricity system, including generation and capacity decisions, supply cost, and emissions over time. Integrating climate warming into the US-REGEN end-use model can be applied in future studies to inform system planners and other stakeholders about electric power systems that are resilient to a range of possible climate, policy, and technology futures.