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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid

RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variable resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.

Etingov, Pavel↗
DOE OSTI2023

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Storm-DEPART (Damage Estimate Prediction and Recovery Tool)

Storm-DEPART (Damage Estimate Prediction and Restoration Tool): Each year hurricanes and tropical storms in the United States damage critical infrastructure assets, disrupt the services they provide, and cause millions to billions of dollars in economic impacts due to extended recovery times. The Storm-DEPART tool and analytical output enable more impactful data-driven decision-making capabilities and strengthen national-level disaster preparedness, response, and recovery. Storm-DEPART, built through multi-month collaboration between Entergy and INL, combines Entergy’s critical infrastructure inventory data with weather forecasts to predict damages to Electric utility’s assets due to natural disasters and the estimated recovery support needed, including time, materials, and resource allocation. In the event of an approaching hurricane, this innovative solution can assess potential damage to power generation capacity, transmission grids, distribution networks, and communications assets from wind bands, storm surge, and flooding. With more effective predictions, Entergy can more efficiently allocate resources to mitigate impacts and optimize recovery for customers. Storm-DEPART also allows Electric utilities the ability to apply a planning scenario and model expected damage to better inform infrastructure restoration needs leading to enhance system resiliency. The technology is fully transferrable to other electric utilities with the same damage estimating challenges. The INL team is working on the evolution of Storm-DEPART to include ice event damage prediction framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A life cycle assessment of e-hydrogen production using proton-exchange membrane water electrolysis coupled with desalination in Saudi Arabia

Hydrogen, considered a crucial element in the transition towards a sustainable energy future, offers the potential to mitigate greenhouse gas (GHG) emissions and reduce reliance on fossil fuels. Here, this study explores the viability of hydrogen production using proton exchange membrane water electrolysis (PEMWE) as a key driver of decarbonization within the Vision 2030 framework in the Kingdom of Saudi Arabia. A first-of-a-kind life cycle assessment (LCA) of electrolytic hydrogen (e-hydrogen) production using PEMWE in the Kingdom is performed. As the hydrogen will be produced in a freshwater scarce region, the inclusion of water desalination processes adds an important dimension to the assessment, reflecting the local context and resource availability. Two main renewable energy scenarios are assessed: solar energy through photovoltaics (PV) and wind energy through onshore turbines. The global warming potential (GWP) results indicate a GHG emissions reduction of up to 95 % compared to the state-of-the-art steam methane reforming process if the electrolysis process is powered exclusively by renewable electricity. The scenarios powered by solar and wind energy result in 3.66 and 0.76 kg CO 2 eq/kg H 2 , respectively. The metal depletion is assessed to consider the requirement of rare materials, with a 7.19 × 10 −2 kg Cu eq/kg H 2 for the solar scenario and 2.82 × 10 −2 kg Cu eq/kg H 2 for the wind scenario. A contribution analysis reveals that the majority of emissions in both scenarios originate from the electricity used for electrolysis, with the electrolyser itself contributing minimally. The absolute impact of the water desalination process is the same in both scenarios; however, it appears more prominent in the wind-powered case due to the significantly lower overall emissions in that scenario. The findings underscore the importance of renewable energy integration and process optimization in minimizing environmental impacts and advancing the sustainability of e-hydrogen production.

08 HYDROGEN↗
DOE OSTI2023

Power Supply Options for the Marpi Landfill, Saipan: Feasibility Study

The Marpi Landfill, located on the northern end of the island of Saipan in the Commonwealth of the Northern Mariana Islands (CNMI), is powered by an on-site diesel generator that only operates when the landfill is open and staffed. The CNMI Office of Planning and Development (OPD) aspires to provide the Marpi Landfill with 24-hour power availability despite its remote location and to increase the use of sustainable energy within the CNMI. CNMI has a 20% target for renewable energy consumption, as documented in Sustainable Development Goal #7 in the Comprehensive Sustainable Development Plan (OPD 2021) and the renewable portfolio standard (GPO 2014). To accomplish these goals, the U.S. Department of Energy, through its Interagency Reimbursable Work Agreement with the Federal Emergency Management Agency, funded this feasibility study to assess and prioritize power supply options for the landfill. The availability of solar and wind resources varies seasonally, as does the load. A BESS can help to balance mismatches between generation and load on short (hourly or daily) timescales, but not across seasons. The microgrid scenarios evaluated for Marpi consider options for technology combinations that will both meet the load and utilize available resources, despite the challenge presented by higher loads and lower solar and wind availability during the rainy season, depicted in Figure ES-2. The seven scenarios evaluated are summarized in Table ES-1. Each scenario’s configuration was optimized to include component capacities that reduce capital and operating costs, meet the load, and minimize carbon emissions, as feasible. The costs and levelized cost of energy (LCOE) shown do not assume the use of any grant funding or incentives, although these options were also evaluated. To assist with decision-making, a prioritization matrix (Table ES-3) was created to compare the microgrid scenarios evaluated in this feasibility study according to various stakeholder priorities. The prioritization metrics were chosen based on discussions with OPD and will be finalized through stakeholder feedback. The scenarios were given a score between 1 and 7 for each prioritization metric (the lower the score, the higher the priority), and total scores were calculated using assigned weights based on the relative priority of each metric. The total scores were then ranked to produce a prioritized list of microgrid scenarios based on the metrics most important to the project stakeholders. As shown, scenario 4 (100 kW of solar PV, a 75 kW/300 kWh BESS, and 160 kW of diesel generation) ranks highest.

14 SOLAR ENERGY↗
DOE OSTI2015

Budget Period 2 Summary Report Part 2: Hywind Maine Project

This project was performed under the Work for Others—Funds in Agreement FIA-14-1793 between Statoil and the Alliance for Sustainable Energy, manager and operator of the National Renewable Energy Laboratory (NREL). To support the development of a 6-MW spar-mounted offshore wind turbine, Statoil funded NREL to perform tasks in the following three categories: 1. Design and analysis 2. Wake modeling 3. Concept resource assessment. This study expands upon the work conducted in Budget Period 1 (BP1) to investigate the influence of the wake generated from an upstream turbine on a downstream turbine using Computational Fluid Dynamics (CFD) high-fidelity modeling tool. Simulator fOr Wind Farms Application (SOWFA) is an NREL high fidelity modeling tool that couples OpenFOAM CFD and NREL’s Aero-Elastic code Fatigue, Aerodynamics, Structures, and Turbulence (FAST). In BP1 the configuration was based on Hywind-3MW at 140 m water depth in the Gulf of Maine; however this study for Budget Period 2 (BP2) the configuration investigated is based on Hywind-6MW at 220 m water depth off the coast of Boston. The objectives were to perform two-turbines One-Way Coupling (OWC), three-turbines Two-Way Coupling (TWC), and to investigate wind power plant optimization.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

University of Oregon: GPS-based Precipitable Water Vapor (PWV)

A partnership with the University of Oregon and U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to collect Precipitable Water Vapor (PWV) data to complement existing resource assessment data collection by the university.

17 WIND ENERGY↗
DOE OSTI2022

Offshore reanalysis wind speed assessment across the wind turbine rotor layer off the United States Pacific coast

Abstract. The California Pacific coast is characterized by considerable wind resource and areas of dense population, propelling interest in offshore wind energy as the United States moves toward a sustainable and decarbonized energy future. Reanalysis models continue to serve the wind energy community in a multitude of ways, and the need for validation in locations where observations have been historically limited, such as offshore environments, is strong. The U.S. Department of Energy (DOE) owns two lidar buoys that collect wind speed observations across the wind turbine rotor layer along with meteorological and oceanographic data near the surface to characterize the wind resource. Lidar buoy data collected from recent deployments off the northern California coast near Humboldt County and the central California coast near Morro Bay allow for validation of commonly used reanalysis products. In this article, wind speeds from the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), the Climate Forecast System version 2 (CFSv2), the North American Regional Reanalysis (NARR), the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), and the analysis system of the Rapid Refresh (RAP) are validated at heights within the wind turbine rotor layer ranging from 50 to 100 m. The validation results offer guidance on the performance and uncertainty associated with utilizing reanalyses for offshore wind resource characterization, providing the offshore wind energy community with information on the conditions that lead to reanalysis error. At both California coast locations, the reanalyses tend to underestimate the observed rotor-level wind resource. Occasions of large reanalysis error occur in conjunction with stable atmospheric conditions, wind speeds associated with peak turbine power production (> 10 m s−1), and mischaracterization of the diurnal wind speed cycle in summer months.

17 WIND ENERGY↗
DOE OSTI2016

Capacity value assessments of wind power

This article describes some of the recent research into the capacity value of wind power. With the worldwide increase in wind power during the past several years, there is increasing interest and significance regarding its capacity value because this has a direct influence on the amount of other (nonwind) capacity that is needed. We build on previous reviews from IEEE and IEA W ind T ask 25 a and examine recent work that evaluates the impact of multiple‐year data sets and the impact of interconnected systems on resource adequacy. We also provide examples that explore the use of alternative reliability metrics for wind capacity value calculations. We show how multiple‐year data sets significantly increase the robustness of results compared to single‐year assessments. Assumptions regarding the transmission interconnections play a significant role. To date, results regarding which reliability metric to use for probabilistic capacity valuation show little sensitivity to the metric. WIREs Energy Environ 2017, 6:e226. doi: 10.1002/wene.226 This article is categorized under: Wind Power > Economics and Policy Wind Power > Systems and Infrastructure Energy Infrastructure > Economics and Policy

Milligan, Michael↗
DOE OSTI2025

Reliability Analysis of Power Grids Considering Component Failures of Variable Energy Resources

This paper proposes an improved model for the reliability assessment of power systems considering component failures of variable energy resources (VER). The inherent intermittency of VER such as solar photovoltaic (PV) and wind farms, along with their susceptibility to component failures, present significant challenges to reliable system operation. These issues, combined with power grid operation and network constraints, complicate the reliable operation of VER-integrated power systems. Here, to address these concerns, this paper introduces a reliability assessment framework that considers VER input variability, its impact on component availability, and their resulting impact on overall system reliability. Stochastic models based on discrete Markov processes are developed to incorporate variable irradiance, wind speeds, and their effects on PV and wind component failure rates. A next-event and state transition-based approach is then developed to integrate the stochastic models into a mixed-timing sequential Monte Carlo simulation framework for composite reliability assessment. Case studies on the RTS-GMLC system demonstrate the effectiveness of the proposed model in evaluating the reliability of VER-integrated systems.

Pandit, Dilip [Sandia National Laboratories (SNL-N↗
DOE OSTI2015

Wildlife Densities and Habitat Use Across Temporal and Spatial Scales on the Mid-Atlantic Outer Continental Shelf. Final Report to the Department of Energy EERE Wind & Water Power Technologies Office

The Mid-Atlantic Baseline Studies Project helped address environmental barriers to offshore wind energy development in the mid-Atlantic region by providing regulators, developers, and other stakeholders with comprehensive baseline ecological data and analyses. Project funders and collaborators from a range of academic institutions, non-governmental organizations, federal agencies, foundations, and private companies came together to study bird, sea turtle, and marine mammal distributions, densities, and movements on the mid-Atlantic Outer Continental Shelf between 2012 and 2014. Specific project activities and goals included the following: (1) Conduct standardized surveys to quantify bird, sea turtle, and marine mammal densities seasonally and annually throughout the study region and identify important habitat use or aggregation areas. (2) Develop statistical models to help understand the drivers of wildlife distribution and abundance patterns. (3) Use individual tracking data for several focal bird species to provide information on population connectivity and individual movements that is complementary to survey data. (4) Identify species that are likely to be exposed to offshore wind energy development activities in the mid-Atlantic study area. (5) Develop U.S.-based technological resources and assessment methods for future monitoring efforts, including a comparison of high resolution digital video aerial surveys to boat-based surveys. (6) Help meet data needs associated with National Environmental Policy Act (NEPA), Marine Mammal Protection Act, and Endangered Species Act requirements, by contributing several years of data and analysis towards future Environmental Impact Statements. This report consists of six parts: Project overview (executive summary and Chapters 1-2); Examining wildlife distributions and relative abundance from a digital video aerial survey platform (Chapters 3-6); Examining wildlife distributions and abundance using boat-based surveys (Chapters 7-12); Integrating data across survey platforms (Chapters 13-19); Individual movements and habitat use for focal bird species (Chapters 20-25); and Nocturnal avian migration monitoring (Chapters 26-27). Boat-based and digital video aerial surveys each had specific advantages and disadvantages, but were largely complementary (Chapters 1, 5, 13-14). Digital aerial surveys were particularly useful for covering offshore areas at broad scales, where general distributions of taxonomic groups were a priority; boat surveys could provide more detailed data on species identities and behaviors, but were more limited in geographic scope due to their slower survey pace. The mid-Atlantic study area was important for wintering and breeding taxa, and its location also made it a key migratory corridor. There was considerable variation in species composition and spatial patterns by season, largely driven by dynamic environmental conditions (Chapters 12, 15, and 20-22). Habitat gradients in nearshore waters, however, were reliable influences on productivity and patterns of species distributions and abundance. Areas within about 30-40 km of the coast offshore of the mouths of Chesapeake and Delaware Bays, as well as to the south of Delaware Bay along the coast, were consistent hotspots of abundance and species diversity, regardless of survey methodology or analytical approach (Chapters 2, 12, 17). Inter-annual variation was substantial, and the importance of certain environmental variables in predicting animal distributions indicates that these species may well respond to future environmental shifts brought about by anthropogenic effects and climatic change. This study is an important first step, however, towards understanding how bird, marine mammal, and sea turtle populations in the mid-Atlantic may be exposed to offshore wind energy development and other anthropogenic activities. The results of this study provide insight to help address environmental permitting requirements for current and future offshore development projects, and serve as a starting point for more site-specific studies, risk analyses, and evaluation of potential measures to avoid and minimize those risks.

17 WIND ENERGY↗
DOE OSTI2025

A Practical Approach to Inertia Assessment: Analyzing New York's Grid Response to Real Events

The non-uniform distribution of inverter-based resources (IBRs) such as solar and wind energy leads to the formation of weakly coupled regions within the broader interconnection. This highlights the urgency of investigating regional dynamics. This paper proposes a practical framework for estimating regional inertia using actual event measurements from the New York (NY) region. The regional frequency is determined using measurement data from frequency disturbance recorders (FDRs) deployed across NY. The rate-of-change of frequency (RoCoF) is estimated using a hybrid methodology that combines the benefits of both moving and non-moving window techniques. By utilizing the power mismatch value and the estimated RoCoF, various inertia metrics such as regional RoCoF, inertia arrival time, and inertia percentage relative to the interconnection inertia are calculated. The identified confirmed-events that took place between 2017–2022 in NY are used in the study. This assessment of inertia using real event data reveals the true behavior of the grid under stress. The results indicate that as the generation mix in NY evolves with the rise of IBRs, both the RoCoF levels and the regional inertia undergo significant changes.

Dulal, Saurav [University of Tennessee, Knoxville ↗
DOE OSTI2024

Development of typical solar years and typical wind years for efficient assessment of renewable energy systems across the U.S.

Weather data plays a critical role in renewable energy analysis. Compared to using multiple Actual Meteorological Years, simulations using a single typical year require significantly fewer computational resources. Previous efforts to create typical weather datasets for renewable energy analysis either lack justified or optimized strategies for selecting and weighting different weather parameters or are limited to a few specific locations. Here, in this study, we developed a dataset comprising Typical Solar Years (TSYs) and Typical Wind Years (TWYs) for over 2000 locations across the U.S., based on data from NASA's POWER project. The strategies for creating TSYs and TWYs were optimized based on the simulated outputs of various PV systems and wind turbines in 16 representative cities. This dataset provides an efficient means for the rapid evaluation and optimization of renewable energy systems throughout the entire U.S. Additionally, the optimal strategies identified in this study can be directly applied to create near-optimal TSYs and TWYs for most locations worldwide. However, readers can also employ the optimization approach presented in this work to develop optimal strategies tailored for particular regions.

NASA POWER↗
DOE OSTI2018

The impact of planning reserve margins in long-term planning models of the electricity sector

The planning reserve margin is the predominant metric used in long-term planning models to ensure the resource adequacy of projected power systems. Considerable work has been done to estimate the contribution of variable renewable energy resources, such as wind and solar, to the planning reserve margin, but little work has been done to assess what planning reserve margin should be used in planning models. Typically, U.S.-based models use the North American Electric Reliability Corporation (NERC)-recommended reserve margin levels. However, historical reserve margins have often exceeded the NERC-recommended levels, suggesting that the use of NERC-recommended levels in planning models may negatively bias projected future capacity investments relative to real-world trends. Using the Regional Energy Deployment System capacity expansion model, we show that setting the planning reserve margin to observed levels in lieu of the NERC-recommended levels leads to substantial differences in near-term capacity additions. Scenarios using alternative specifications for the reserve margin resulted in increased national solar builds of 20-100 GW. Given that the magnitude on results from altering the reserve margin level is similar to or greater than many policies frequently analyzed with planning models, careful consideration of the reserve margin level is crucial for developing accurate power sector projections.

24 POWER TRANSMISSION AND DISTRIBUTION↗
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 OSTI2015

LCOE Uncertainty Analysis for Hydropower using Monte Carlo Simulations

Levelized Cost of Energy (LCOE) is an important metric to evaluate the cost and performance of electricity production generation alternatives, and combined with other measures, can be used to assess the economics of future hydropower development. Multiple assumptions on input parameters are required to calculate the LCOE, which each contain some level of uncertainty, in turn affecting the accuracy of LCOE results. This paper explores these uncertainties, their sources, and ultimately the level of variability they introduce at the screening level of project evaluation for non-powered dams (NPDs) across the U.S.Owing to site-specific differences in site design, the LCOE for hydropower varies significantly from project to project unlike technologies with more standardized configurations such as wind and gas. Therefore, to assess the impact of LCOE input uncertainty on the economics of U.S. hydropower resources, these uncertainties must be modeled across the population of potential opportunities. To demonstrate the impact of uncertainty, resource data from a recent nationwide non-powered dam (NPD) resource assessment (Hadjerioua et al., 2012) and screening-level predictive cost equations (O’Connor et al., 2015) are used to quantify and evaluate uncertainties in project capital and operations & maintenance costs, and generation potential at broad scale. LCOE dependence on financial assumptions is also evaluated on a sensitivity basis to explore ownership/investment implications on project economics for the U.S. hydropower fleet.The results indicate that the LCOE for U.S. NPDs varies substantially. The LCOE estimates for the potential NPD projects of capacity greater than 1 MW range from 40 to 182 $/MWh, with average of 106 $/MWh. 4,000 MW could be developed through projects with individual LCOE values below 100 $/MWh. The results also indicate that typically 90 % of LCOE uncertainty can be attributed to uncertainties in capital costs and energy production; however, for small projects (below 10 MW) O&M uncertainty plays an important role. The potential NPDs have costs with uncertainty bands extending well above 100 $/MWh in some cases. A truly representative evaluation should complement LCOE with an assessment of potential revenues from the provision of ancillary services. Moreover, hydroelectric production is often part of multipurpose water resource projects where other purposes (e.g., irrigation, flood control, navigation, recreation, etc.) also provide value. Neither of these considerations are accounted for LCOE.

Chalise, Dol Raj↗
DOE OSTI2016

Wholesale electricity market design with increasing levels of renewable generation: Revenue sufficiency and long-term reliability

This paper discusses challenges that relate to assessing and properly incentivizing the resources necessary to ensure a reliable electricity system with growing penetrations of variable generation (VG). The output of VG (primarily wind and solar generation) varies over time and cannot be predicted precisely. Therefore, the energy from VG is not always guaranteed to be available at times when it is most needed. This means that its contribution towards resource adequacy can be significantly less than the contribution from traditional resources. Variable renewable resources also have near-zero variable costs, and with production-based subsidies they may even have negative offer costs. Because variable costs drive the spot price of energy, this can lead to reduced prices, sales, and therefore revenue for all resources within the energy market. The characteristics of VG can also result in increased price volatility as well as the need for more flexibility in the resource fleet in order to maintain system reliability. Furthermore, we explore both traditional and evolving electricity market designs in the United States that aim to ensure resource adequacy and sufficient revenues to recover costs when those resources are needed for long-term reliability. We also investigate how reliability needs may be evolving and discuss how VG may affect future electricity market designs.

17 WIND ENERGY↗