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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 OSTI2022

Investigating capacity credit sensitivity to reliability metrics and computational methodologies

Assigning capacity value to renewable energy sources (RES) is a challenge faced in planning their integration with the grid. The difficulties stem from the natural characteristics of variability and intermittency of wind and solar sources. The capacity credit (CC) analysis evaluates the system’s actual power output compared with a constant capacity generator, i.e., conventional generator and determines an effective capacity to use for planning and operation. Herein this paper presents different factors that could affect the CC of a system. Two methods are proposed to determine the CC, namely equivalent firm capacity (EFC) and effective load carrying capability (ELCC). Since these methods are based on satisfying reliability criteria, daily loss of load expectation (LOLE), hourly loss of load (LOLH), and expected energy not served (EENS) have been employed as indices. To obtain the CC value, both methods apply two techniques: traditional and optimization. Genetic algorithm (GA) is the optimization approach used in this paper. Then, this work compares the two techniques and shows the superior performance of the optimization approach. Two hybrid systems, stand-alone (SA) and grid-connected (GC) modes, are proposed and used as case studies. The hybrid systems consist of photovoltaic (PV), wind turbine (WT), and battery energy storage system (BESS). In this work, three different scenarios are used to compare capacity credit: system as a whole, only wind, and no batteries. Finally, sensitivity analysis is carried out to examine the impact of varying the wind speed, solar irradiation, and load. It is demonstrated that the choice of reliability index plays an important role in determining the capacity credit and it is shown that EENS is a more comprehensive and consistent index of reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Average and Marginal Capacity Credit Values of Renewable Energy and Battery Storage in the United States Power System

As deployment of renewable resources and storage continue to significantly grow in the coming decades, these technologies will play increasingly important roles in maintaining power systems' resource adequacy. Few analyses so far offer comprehensive comparisons of forward-looking average and marginal capacity credits of variable renewable energy and storage in the U.S. interconnections across a wide range of possible futures. To fill this research gap, we quantify the average and marginal capacity credits of solar PV, onshore and offshore wind, and batteries between 2026 and 2050 across the U.S power systems to examine the temporal trends, spatial patterns, and trade-offs between these two capacity accreditation approaches. Across technologies, capacity credits of solar PV most clearly follow downward trends over time, reflecting the significant rise in solar PV generation share as the grid decarbonizes. While battery storages' generation shares also rise significantly over time, their capacity credits always remain stably high due to their capabilities to be dispatched strategically during critical periods to maintain reliability. On the other hand, capacity credits of wind technologies in general follow slight upward trends as their generation shares level off. There are strong spatial variabilities of both average and marginal capacity credits across technologies, but capacity credits of solar PV displaying the most obvious spatial patterns with high capacity credits concentrating in wind-rich, solar-poor regions in SPP, PJM, and MISO, suggesting potential reliability benefits of interconnection-wide planning for renewable energy deployments. Additionally, except for offshore wind, average capacity credits of all other renewable technologies tend to be higher than their marginal capacity credits, indicating that existing renewable resources tend to be accredited higher than new resources at almost any time.

25 ENERGY STORAGE↗
DOE OSTI2023

Impacts of hybridization and forecast errors on the probabilistic capacity credit of batteries

Battery storage is increasingly identified as being among the least-cost mix of technologies in the evolving U.S. electricity mix. This study explores the marginal capacity credit of batteries using a probabilistic, reliability-based, effective firm capacity method, which we apply for multiple battery power ratings, durations, coupling types, deployment locations, and dispatch profiles within a test system that is based on the Texas Interconnection in the year 2024. We find that the capacity credits for all battery durations depend on their ability to predict the timing of reliability events. Even 1-2 h forecast errors - resulting in early or delayed battery discharging relative to the onset of a reliability event - lead pronounced capacity credit reductions, especially for 4-h duration batteries. Coupling batteries with solar mitigates the uncertainty associated with a shorter-duration battery's availability during reliability events, primarily due to the relatively high solar capacity credit in our test system. Coupled (or hybrid) system designs with oversized solar arrays, the ability to charge the coupled battery with grid energy, and larger batteries lead to the greatest capacity credit benefits of hybridization. We do not see evidence that the hybrid capacity credit exceeds the sum of the separate battery and solar capacity credits.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A simple and fast algorithm for estimating the capacity credit of solar and storage

Energy storage is a leading option to enhance the resource adequacy contribution of solar energy. Detailed analysis of the capacity credit of solar energy and energy storage is limited in part due to the data intensive and computationally complex nature of probabilistic resource adequacy assessments. This paper presents a simple algorithm for calculating the capacity credit of energy-limited resources that, due to the low computational and data needs, is well suited to exploratory analysis. Validation against benchmarks based on probabilistic techniques shows that it can yield similar insights. The method is used to evaluate the impact of different solar and storage configurations, particularly with respect to the strategy for coupling storage and solar photovoltaic systems. Furthermore, application of the method to a case study of utilities in Florida, where solar is rapidly growing and demand peaks in the winter and summer, demonstrates that it can improve on rules of thumb used in practice by some utilities. If storage is required to charge only from solar, periods of high demand driven by cold weather events accompanied by lower solar production can result in a capacity credit of solar and storage that is less than the capacity credit of storage alone.

14 SOLAR ENERGY↗
DOE OSTI2021

A systematic evaluation of wind's capacity credit in the Western United States

Abstract The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), can be impacted by many factors. The CC varies regionally with wind resource and correlation to net load and may also vary with wind technology (land‐based versus offshore) and turbine specifications. We use a probabilistic resource adequacy tool to systematically assess the CC of multiple technologies for near‐term wind deployment across the Western US power system to help inform planning decisions. We find that wind CC varies by weather year and location but averages 16% for land‐based turbines and 41% for offshore turbines, with large regional variations. The average wind CC increases to 20% for land‐based and 53% for offshore when considering only the sites in the top 25th percentile of capacity factor. The CC of land‐based wind is generally lower than its capacity factor, which indicates a low correlation of generation to system needs. However, offshore wind shows a substantially higher CC, which is driven by not only a higher capacity factor but also a greater correlation with system needs.

17 WIND ENERGY↗
DOE OSTI2021

Comparing Capacity Credit Calculations for Wind: A Case Study in Texas

The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), varies regionally with wind resource and correlation to net load. CC is an important metric widely used for resource planning and resource adequacy assessments. However, there are multiple methods for computing and estimating CC, depending on specific needs, access to data, and computational burden. It is unclear the extent to which the CC computation method may influence the result. To address this, we use a probabilistic resource adequacy tool and multiple approximation methods to systematically assess the CC of wind for near-term wind deployment under a case study in Texas. We find that proper consideration of transmission constraints is important; some approximation methods may overestimate the CC of wind due to a lack of consideration of transmission constraints, while other approximation methods may underestimate the CC by not capturing the ability of wind to be shipped to neighboring regions. In this case study, we find that several approximation methods do come close to the CC calculated by more robust probabilistic methods. However, the best approximation method may vary on a case-by-case basis, depending on system-specific considerations.

17 WIND ENERGY↗
DOE OSTI2024

Beyond Capacity Credits: Adaptive Stress Period Planning for Evolving Power Systems

This paper combines and applies concepts from several researchers to outline an alternative framework to plan power systems for resource adequacy needs, which we call Adaptive Stress Period Planning (ASPP). It first provides background information regarding least-cost planning objectives and the challenge of balancing an increasing need for model representation with computational intensity as power systems evolve in complexity. Next, it motivates the opportunity for a new paradigm by outlining challenges of frameworks in use today that rely on aggregate capacity heuristics (i.e., capacity credits and planning reserve margins). Subsequently, it lays out main process details of ASPP, which more directly represents spatial and temporal dynamics of power systems in a capacity expansion model with a process to adaptively select risk periods. The paper concludes with a summary of the approach, its benefits, and opportunities for future work.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value for 2012-2020

Lawrence Berkeley National Laboratory (Berkeley Lab) estimates hourly project-level generation data for utility-scale solar projects and hourly county-level generation data for residential and non-residential distributed photovoltaic (PV) systems in the seven organized wholesale markets and 10 additional Balancing Areas. To encourage its broader use, Berkeley Lab has made this data file public here at OEDI, covering the years 2012-2020. The public project-level dataset is updated annually with data from the previous calendar year. For more information about the research project, including a technical report, briefing material, visualizations, and additional data, please visit the project homepage linked in this submission.

annual solar value↗
DOE OSTI2020

Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value

Lawrence Berkeley National Laboratory (Berkeley Lab) estimates hourly project-level generation data for utility-scale solar projects and hourly county-level generation data for residential and non-residential distributed photovoltaic (PV) systems in the seven organized wholesale markets and 10 additional Balancing Areas. To encourage its broader use, Berkeley Lab has made this data file public here at OEDI. The public project-level dataset is updated annually with data from the previous calendar year. For more information about the research project, including a technical report, briefing material, visualizations, and additional data, please visit the project homepage linked in this submission. A newer version of the data exists and can be found linked in the resources of this submission under "Solar-to-Grid Public Data File Updated 2021".

annual solar value↗
DOE OSTI2022

Impact of Storage Dispatch Assumptions on Resource Adequacy and Capacity Credit

Representing energy-limited resources in power system probabilistic resource adequacy assessment introduces new considerations that invalidate classical modeling assumptions. In particular, such resources have multi-period operating objectives and constraints that in real systems are addressed via a sequence of rolling intertemporal optimizations. Ideally, adequacy models would develop dispatch decisions by solving a similar sequence of problems, but this approach has historically been too computationally intensive for practical use in Monte Carlo simulations, with studies making use of simplifying approximations instead. These simplifications have the potential to distort the assessed value of energy-limited resources on the system.This work describes three classes of storage dispatch assumptions in current use and discusses their theoretical differences. It then provides an empirical analysis of their differences on test systems with different levels of storage, assessing the potential for a study's modeling assumptions to influence the perceived contribution of energy-limited resources.

capacity credit↗
DOE OSTI2026

Solar and Storage Integration in the U.S. Southeast: Implications for Resource Adequacy [Slides]

In this study, we evaluate how an iterative portfolio approach compares to a more traditional capacity credit method, using the U.S. Southeast as a case study region. Using open-source planning and resource adequacy tools, we compare results using a capacity credit approximation method with those from iterating behind the two. We also explore how the iterative approach performs under a range of sensitivities, including higher load growth, regional coordination, and alternative weather years. We find that traditional capacity credit approximation methods can function well in today's system, but may face challenges for systems with higher levels of solar and storage. As such, integrating planning and resource adequacy models can address some of these gaps, helping planners deliver more reliable systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Additional Capacity Value From Synergy of Variable Renewable Energy and Energy Storage

Current capacity markets often consider capacity credits from each resource independently, irrespective of the portfolio of resources, potentially overvaluing or undervaluing the capacity contribution of variable renewable energy (VRE) and energy storage (ES) in the grid. We propose a method for calculating the standalone and integrated capacity value of an added VRE resource with existing ES resources. The difference between the integrated and standalone value is the portfolio effect. This is the additional capacity value gained by the synergy of VRE and the existing fleet. Using chronological dispatch simulations and two different reliability metrics to estimate firm capacity, we demonstrate on a small test system that the portfolio effect can be substantial.

capacity credit↗
DOE OSTI2021

Reliability Barriers to Enhanced Solar PV Deployment: Selected Research Findings - State Outreach Technical Sessions

This presentation provides summaries of three reports selected from a body of work that examines potential reliability challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations in the western United States. The three topics covered are 1) Power system flexibility requirements and supply; 2) Resource adequacy and the capacity credit of solar; 3) Simulating distributed energy resource responses to transmission system-level faults considering IEEE 1547 performance categories on three major WECC transmission paths. The full reports and related resources are available at the project website, https://www.westernenergyboard.org/western-interstate-energy-board/barrier-mitigation-to-enhanced-distributed-solar-photovoltaic/. This presentation is targeted toward a technical audience. A companion policy presentation provides higher-level summaries of the same material.

distributed energy resource↗
DOE OSTI2021

Reliability Barriers to Enhanced Solar PV Deployment: Selected Research Findings - State Outreach Policy Sessions

This presentation provides high-level summaries of three reports selected from a body of work that examines potential reliability challenges related to planning future power systems with higher solar photovoltaic (PV) penetrations in the western United States. The three topics covered are 1) Power system flexibility requirements and supply; 2) Resource adequacy and the capacity credit of solar; 3) Simulating distributed energy resource responses to transmission system-level faults considering IEEE 1547 performance categories on three major WECC transmission paths. The full reports and related resources are available at the project website, https://www.westernenergyboard.org/western-interstate-energy-board/barrier-mitigation-to-enhanced-distributed-solar-photovoltaic/. This presentation is targeted toward policy decision makers. A companion technical presentation provides more in-depth summaries of the same material.

distributed energy resource↗
DOE OSTI2023

Hybrid renewable energy systems: the value of storage as a function of PV-wind variability

As shares of variable renewable energy (VRE) on the electric grid increase, sources of grid flexibility will become increasingly important for maintaining the reliability and affordability of electricity supply. Lithium-ion battery energy storage has been identified as an important and cost-effective source of flexibility, both by itself and when coupled with VRE technologies like solar photovoltaics (PV) and wind. In this study, we explored the current and future value of utility-scale hybrid energy systems comprising PV, wind, and lithium-ion battery technologies (PV-wind-battery systems). Using a price-taker model with simulated hourly energy and capacity prices, we simulated the revenue-maximizing dispatch of a range of PV-wind-battery configurations across Texas, from the present through 2050. Holding PV capacity and point-of-interconnection capacity constant, we modeled configurations with varying wind-to-PV capacity ratios and battery-to-PV capacity ratios. We found that coupling PV, wind, and battery technologies allows for more effective utilization of interconnection capacity by increasing capacity factors to 60%–80%+ and capacity credits to close to 100%, depending on battery capacity. We also compared the energy and capacity values of PV-wind and PV-wind-battery systems to the corresponding stability coefficient metric, which describes the location-and configuration-specific complementarity of PV and wind resources. Our results show that the stability coefficient effectively predicts the configuration-location combinations in which a smaller battery component can provide comparable economic performance in a PV-wind-battery system (compared to a PV-battery system). These PV-wind-battery hybrids can help integrate more VRE by providing smoother, more predictable generation and greater flexibility.

14 SOLAR ENERGY↗