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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Data-Based Resilience Enhancement Strategies for Electric-Gas Systems Against Sequential Extreme Weather Events

Some extreme weather events, such as the hurricane, pass through an area sequentially and thus are called sequential extreme weather events (SEWEs). This paper proposes a data-based robust optimization (RO) model to enhance the resilience of the integrated electricity and gas system (IEGS) against SEWEs. Specifically, the SEWE strikes the IEGS sequentially. After each attack, the system state is adjusted immediately to minimize the maximized expected system cost caused by the SEWE. The attack-defense procedures are repeated alternatively during the SEWE. Preventive measures, hardening, are made in advance to reduce the impact of sequential attacks. The entire process is formulated as a multi-period RO model. Furthermore, it is proved that the most effective resilience enhancement strategies for this model are the same as those for a two-stage RO model, which can be solved by the nested column-and-constraint generation (C&CG) algorithm. In addition, the property of SEWEs, sequentially endangering limited regions of the IEGS, is incorporated to build a data-based uncertainty set and reduce its conservativeness. Simulation results on two IEGSs validate the effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Extreme Weather Events and PV Systems Impact

The impact of extreme weather events on PV performance was studied by comparing the National Oceanic and Atmospheric Administration database on severe weather with the National Renewable Energy Laboratory's (NREL) PV Fleet database on continuous PV performance. We identified 170 systems that were immediately impacted by weather events. These severe weather events lead to a median loss of only 1 % of annual production. However, flooding and high wind events were found to have an extremely long tail extending to 60 % loss, showing that these discrete events can pose a substantial risk to PV systems. Besides the short-term impact of lost production due to outages, we also found a statistically significant increased performance loss rate (PLR) for high wind events above 90 kilometer/hour, by comparing PLR before and after these events. Similarly, hail events caused higher PLR for hail sizes of and above 25 mm indicating that more stringent hail testing for PV modules is required. In addition, very high snow loads may also cause increased PLRs, but more data are required to better quantify the impact. These findings illustrate the substantial risk extreme weather events pose short-and long-term to fielded PV installations.

extreme weather↗
DOE OSTI2023

Extreme Weather Events and the Impact on PV Time Series Data

The impact of extreme weather events on PV performance was studied by comparing the National Oceanic and Atmospheric Administration database on severe weather with the PV Fleet database on continuous PV performance. We identified 170 systems that were immediately impacted by weather events. These severe weather events lead to a median loss of only 1% of annual production. However, flooding and high wind events were found to have an extremely long tail extending to 60 % loss showing that these discrete events can pose a substantial risk to PV systems. Besides the short-term impact of lost production due to outages, we also found a statistically significant increased performance loss rate (PLR) for high wind events comparing PLR before and after these weather events. In addition, hail events caused a higher PLR for 2 out of 3 systems. More data are required to better quantify the impact, but these first results illustrate the substantial risk these events pose short-and long-term.

degradation↗
DOE OSTI2021

Impact of Extreme Weather Events on Physical Protection System Effectiveness for a Hypothetical Small Modular Reactor Facility: Systems Analysis and Considerations

This report will summarize the group's work to provide recommendations to secure nuclear facilities before, during and after an extreme weather event. Extreme weather events can have drastic impacts to nuclear facilities as seen by the earthquake and subsequent tsunami at the Fukushima Daiichi Nuclear Power Plant in 2011. Recent hurricanes in the United States including Hurricane Harvey demonstrate the devastating effects these storms can have on infrastructure and the surrounding communities. The group is attempting to identify the gaps that potential small modular reactor (SMR) facilities will need to address in order to provide adequate site security before, during and after extreme weather events. This effort proceeded in three parts to provide insights and recommendations to secure Small Modular Reactor facilities for extreme weather events:(1) a literature review of academic articles as well as relevant documents including the existing regulatory framework and recommendations from the IAEA, NRC, and DOE, (2) subject matter expert interviews from a wide variety of security backgrounds, and (3) modeling and simulation on a hypothetical SMR facility. Special attention was paid to the interactions between stakeholders and nuclear facility design considerations, particularly the topics of safety and security. Engineering design issues from safety and security perspectives were discussed and included in simulation. Each step informed the proceeding, with the result including full tabletop scenarios of EWE impacts to security system effectiveness on the hypothetical model. This systems-level analysis provides results to inform recommendations to secure SMR facilities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Assessing Historical Extreme Weather Event Impacts

Understanding how past extreme weather events have affected a site is an integral part of site-level resilience planning. Energy and water resilience planning has been a key priority for the federal government for many years and agencies look to develop processes for identifying and addressing critical resilience gaps at their facilities and across their sites. The purpose of this information paper is to help inform how organizations could begin structuring a comprehensive process for recording the impacts of extreme weather events in order to facilitate climate vulnerability assessments, and thus, resilience planning. The paper highlights current limitations for developing event history assessments and suggests a framework for more consistently capturing key data points.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-learning

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure damage in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified to help transmission and distribution system operators prepare for and prevent significant damage and subsequent loss of power. In this paper, we develop an approach that models the impact of extreme weather on the grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch to minimize the adverse impacts of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

distribution system↗
DOE OSTI2021

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-Learning

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure damage in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified to help transmission and distribution system operators prepare for and prevent significant damage and subsequent loss of power. In this paper, we develop an approach that models the impact of extreme weather on the grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch to minimize the adverse impacts of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

extreme weather↗
DOE OSTI2020

Identification of Worst Impact Zones for Power Grids During Extreme Weather Events Using Q-Learning: Preprint

Both the frequency and intensity of extreme weather events have been trending higher in recent years, leading to significant infrastructure loss in the electric grid. The impact of these extreme weather events is desired to be analyzed and quantified in order to help transmission and distribution system operators to prepare and prevent significant losses. In this paper, we developed an approach that models the impact of extreme weather on the power grid and identifies the worst impact zone using Q-learning (a reinforcement learning approach). The identification results reveal grid vulnerability to weather events and provide insights for system operators to help achieve optimal resource allocation and crew dispatch in order to minimize the adverse impact of extreme weather. Simulation studies are conducted on the IEEE 123-node system to demonstrate the performance of the proposed approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Review of the August 1972 and March 1989 (Allen) Space Weather Events: Can We Learn Anything New From Them?

Abstract Updated summaries of the August 1972 and March 1989 space weather events have been constructed. The features of these two events are compared to the Carrington 1859 event and a few other major space weather events. It is concluded that solar active regions release energy in a variety of forms (X‐rays, EUV photons, visible light, coronal mass ejection (CME) plasmas and fields) and they in turn can produce other energetic effects (solar energetic particles (SEPs), magnetic storms) in a variety of ways. It is clear that there is no strong one‐to‐one relationship between these various energy sinks. The energy is often distributed differently from one space weather event to the next. Concerning SEPs accelerated at interplanetary CME (ICME) shocks, it is concluded that the Fermi mechanism associated with quasi‐parallel shocks is relatively weak and that the gradient drift mechanism (electric fields) at quasi‐perpendicular shocks will produce harder spectra and higher fluxes. If the 4 August 1972 intrinsic magnetic cloud condition (southward interplanetary magnetic field instead of northward) and the interplanetary Sun to 1 au conditions were different, a 4 August 1972 magnetic storm and magnetospheric dawn‐to‐dusk electric fields substantially larger than the Carrington event would have occurred. Under these special interplanetary conditions, a Miyake et al. (2012), https://doi.org/10.1038/nature11123 ‐like extreme SEP event may have been formed. The long duration complex 1989 storm was probably greater than the Carrington storm in the sense that the total ring current particle energy was larger.

Tsurutani, Bruce T.↗
DOE OSTI2021

The Evolving Role of Extreme Weather Events in the U.S. Power System with High Levels of Variable Renewable Energy

As weather-dependent renewable generation grows, it is important for power system planning to understand the broad trends and correlations between weather, renewable resources, and load. The traditional planning, performed by utilities and system operators, includes the study of system resource adequacy during peak load periods in the summer and winter to ensure the generation and transmission system is appropriate to meet load. But in a power grid with a high penetration of variable renewable energy (i.e., wind and solar), periods of high risk to system resource adequacy may no longer correspond only to hours of peak load. In particular, high shares of variable renewable energy, even when well-forecasted to inform system operations, can further complicate the stress extreme weather events already place on the grid. They also may lead to changes to the types of weather conditions that are most problematic to system operations and resource adequacy due to widespread and extended deficits of wind and solar generation. Accordingly, the focus of reliability assessments in long-term planning studies may need to evolve in the coming years to more fully incorporate weather events that lead to these deficits. This report seeks to identify these new weather events and understand the characteristics of the events that lead to system risk of future systems with higher penetrations variable renewable energy.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Examination of the Extreme Cold Weather Event Affecting the Power System in Texas - February 2021 [Slides]

This presentation examines the extreme cold weather event that affected the power system in Texas in February 2021. The Texas load-shedding events were caused by a combination of record-high demand and cold weather issues that reduced the output from all types of generation. While some wind turbines were shutting down due to cold temperatures and icing and a lack of cold-weather packages, hourly wind output was accurately predicted. Extreme weather events historically drive grid reliability. Additional examination of more extreme events is needed to understand their impacts on the power system. As a national lab, NREL has the capabilities and facilities to help the industry address these types of challenges. NREL also has significant simulation and analysis capabilities (such as NAERM) that can help understand the impacts of extreme events. NREL also developed the Advanced Research on Integrated Energy Systems (ARIES) Research Platform, which enables evaluation of technologies that smooth grid operations during events like this.

17 WIND ENERGY↗
DOE OSTI2024

Household energy resilience in extreme weather events: An investigation of energy service importance, HVAC usage behaviors, and willingness to pay

Household energy resilience, particularly maintaining essential energy services within an acceptable and affordable level, is critical during extreme weather events (e.g., winter storms, heat waves) with power shortages or outages. However, the research on the importance and acceptable compromise levels of energy services, HVAC usage behavior changes, and willingness to pay (WTP) for energy services during disasters is limited. Therefore, this study investigates the importance and compromise of household energy services, HVAC usage behaviors, and WTP, as three key dimensions of household energy resilience, in both normal days and disaster scenarios through surveys (n=485). First, 12 common residential end-uses are grouped into high, mid, and low-priority services using hierarchical clustering, in which high-priority services (perceived as important and un-compromisable) include food cooking and storage (refrigerator and freezer) and thermal comfort (space heating and cooling), mid-priority services involve water heating and lighting, while low-priority services are mostly related to entertainment and housework (e.g., TV, laundry). Also, HVAC use patterns demonstrate that occupants become more energy conservative during disasters, e.g., reducing durations of running HVAC and adjusting temperature setpoints to save energy. In terms of energy cost, approximately 60% of respondents are willing to pay more to maintain energy services during disasters, although only 13% are prepared to pay over double the normal energy prices. The regression models further reveal that household energy resilience varies across different sociodemographic groups (e.g., age, income, family size) and is impacted by disaster experience and beliefs in clean energy and climate. In conclusion, these research findings provide important perspectives to understand household energy resilience and inform measures for disaster adaptation of households in extreme weather events.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Enhanced Simulation of Atmospheric Blocking in a High‐Resolution Earth System Model: Projected Changes and Implications for Extreme Weather Events

Atmospheric blocking is closely linked to the occurrence of extreme weather events. However, low-resolution Earth system models often underestimate the frequency of blocking, undermining confidence in future projections. Here, in this study, we use the high-resolution Community Earth System Model (CESM-HR; 25 km atm and 10 km ocean) to show that CESM-HR reduces biases in atmospheric blocking for both winter and summer, particularly for events lasting longer than 10 days. This improvement is partly due to reduced sea surface temperature biases at higher resolution. Additionally, applying a bias correction to the 500 hPa geopotential height further enhances blocking frequency simulations, highlighting the crucial role of the mean state. Under the Representative Concentration Pathway 8.5 scenario, CESM-HR projects a decrease in wintertime blocking over regions such as the Euro-Atlantic and Chukchi-Alaska, consistent with previous studies. In contrast, summer blocking is expected to become more frequent and persistent, driven by weakened zonal winds. The blocking center shifts from historical locations over Scandinavia and eastern Russia to central Eurasia, significantly increasing blocking over the Ural region. Summer blocking frequency over the Scandinavia-Ural region may eventually surpass historical winter blocking over the Euro-Atlantic. This increase in summer blocking could exacerbate summer heatwaves in a warming climate, making severe heatwaves, like those observed recently, more common in the future.

Atmospheric blocking↗
DOE OSTI2025

A sequential Attacker-Defender game for distribution systems resilience enhancement against extreme weather events

Improving distribution system resilience against frequent extreme weather events is important for reliable power system operations. Especially when dealing with events such as hurricanes that have short-term predictions, proactive pre-event preparedness plays a vital role in system resilience performance. In this paper, we propose a novel approach to construct pre-event resource allocation plans for system operators to cope with upcoming threats through a sequential attacker-defender game framework. The sequential attacker-defender game is designed to model the interaction between the extreme weather and the system operator. In each round of the game, the attacker and the defender sequentially update their current strategies by accounting for the opponent’s action set. The attacker model is formulated as a bi-level problem to identify the severe outage scenarios, and the defender model is formulated as a two-stage optimization problem to determine the allocation of restoration resources including mobile responsive resources and repair crews. Two scale-reduction strategies are proposed to ensure the scalability of the game scheme. Finally, case studies on the IEEE 33-bus and a 7149-node practical utility system validate the effectiveness of the proposed sequential game and the efficiency of the scale-reduction strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

On the attribution of the impacts of extreme weather events to anthropogenic climate change

Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events’ impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. ‘system breaking’ events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Meta-Level Framework for Evaluating Resilience in Net-Zero Carbon Power Systems with Extreme Weather Events in the United States

Important changes are underway in the U.S. power industry in the way that electricity is sourced, transported, and utilized. Disruption from extreme weather events and cybersecurity events is bringing new scrutiny to power-system resilience. Recognizing the complex social and technical aspects that are involved, this article provides a meta-level framework for coherently evaluating and making decisions about power-system resilience. It does so by examining net-zero carbon strategies with quantitative, qualitative, and integrative dimensions across discrete location-specific systems and timescales. The generalizable framework is designed with a flexibility and logic that allows for refinement to accompany stakeholder review processes and highly localized decision-making. To highlight the framework’s applicability across multiple timescales, processes, and types of knowledge, power system outages are reviewed for extreme weather events, including 2021 and 2011 winter storms that impacted Texas, the 2017 Hurricane Maria that affected Puerto Rico, and a heatwave/wildfire event in California in August 2020. By design, the meta-level framework enables utility decision-makers, regulators, insurers, and communities to analyze and track levels of resilience safeguards for a given system. Future directions to advance an integrated science of resilience in net-zero power systems and the use of this framework are also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Real-time attribution of the influence of climate change on extreme weather events: a storyline case study of Hurricane Ian rainfall

Abstract As the Earth continues to warm due to human greenhouse gas emissions, there is a growing need to efficiently communicate the effect that global warming has on individual extreme weather events. Using a storyline approach, we present a rapid attribution of the increase in rainfall over Florida during Hurricane Ian in 2022 due to climate change as a case study. We find that extreme accumulated rainfall amounts associated with Hurricane Ian increased by 18%, far in excess of what would be expected by Clausius–Clapeyron scaling. The study offers a blueprint for rapid operational climate change attribution statements about extreme storms and other very rare weather events.

Reed, Kevin A. (ORCID:0000000337417080)↗
DOE OSTI2021

How do intermittency and simultaneous processes obfuscate the Arctic influence on midlatitude winter extreme weather events?

Abstract Pronounced changes in the Arctic environment add a new potential driver of anomalous weather patterns in midlatitudes that affect billions of people. Recent studies of these Arctic/midlatitude weather linkages, however, state inconsistent conclusions. A source of uncertainty arises from the chaotic nature of the atmosphere. Thermodynamic forcing by a rapidly warming Arctic contributes to weather events through changing surface heat fluxes and large-scale temperature and pressure gradients. But internal shifts in atmospheric dynamics—the variability of the location, strength, and character of the jet stream, blocking, and stratospheric polar vortex (SPV)—obscure the direct causes and effects. It is important to understand these associated processes to differentiate Arctic-forced variability from natural variability. For example in early winter, reduced Barents/Kara Seas sea-ice coverage may reinforce existing atmospheric teleconnections between the North Atlantic/Arctic and central Asia, and affect downstream weather in East Asia. Reduced sea ice in the Chukchi Sea can amplify atmospheric ridging of high pressure near Alaska, influencing downstream weather across North America. In late winter southward displacement of the SPV, coupled to the troposphere, leads to weather extremes in Eurasia and North America. Combined tropical and sea ice conditions can modulate the variability of the SPV. Observational evidence for Arctic/midlatitude weather linkages continues to accumulate, along with understanding of connections with pre-existing climate states. Relative to natural atmospheric variability, sea-ice loss alone has played a secondary role in Arctic/midlatitude weather linkages; the full influence of Arctic amplification remains uncertain.

Environmental Sciences & Ecology↗