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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↗

Modeling Methods for Capturing System Interactions of Combined Technologies: A Study of PV + Battery

The costs of solar photovoltaics (PV) have been dropping in recent years, leading to increasing installations of solar PV systems and growing interest in how the technology will impact the electric grid at higher penetrations. Additionally, as battery costs decline it becomes important to understand the benefits and limitations of battery storage for the grid as well as potential benefits of co-locating battery storage and PV, particularly within the realm of future system planning. However, it is non-trivial to capture these potential benefits within a linearized capacity expansion model (CEM). This paper presents methodological developments to more fully represent the value and limitations of coupled PV and battery systems (PV + Battery) in CEMs using the Resource Planning Model (RPM), which co-optimizes capacity investments, transmission investments, and reduced-order dispatch in the Western Interconnection of North America through 2045. We use the model to simulate the evolution of the generation and transmission system under two core scenarios - a baseline scenario and a high renewable penetration scenario - coupled with sensitivities assuming low and midline PV and battery cost projections. When incorporating PV + battery, we find that it is important for CEMs to capture the ability of the coupled technology to provide firm capacity and reduce expected curtailment, compared to independent systems. These interactions can have even more dramatic impacts at higher solar penetrations.

14 SOLAR ENERGY↗

Grid Expansion Optimal Planning Tools (GridEO): Manual for Users and Developers

This report describes Grid Expansion Optimal Planning Tools (GridEO). GridEO is a Python package for electric power grid capacity expansion modeling. With GridEO, the user can build and solve instances of the Capacity Expansion Planning (CEP) problem to determine an optimal plan of investment in capacity of various types of power grid equipment.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Impacts of Renewable Energy and Green Hydrogen Policies on Uttar Pradesh's Power Sector Future: Additional Modeling Scenarios to Explore Hydrogen Flexibility [Slides]

This slide deck is part of a broader program focused on supporting Indian states with long-term power system planning. More information about this program can be found at the National Renewable Energy Laboratory's "Supporting India's States With Renewable Energy Integration" web page at https://www.nrel.gov/international/india-renewable-energy-integration.html. The power sector in Uttar Pradesh, India's most populous state, is poised to transform over the next few decades due to a combination of national and state-level policies impacting both the supply and demand of electricity. The Government of Uttar Pradesh has policies and plans to develop in-state solar PV, pumped storage hydropower, and green hydrogen. Power system policymakers and utilities in Uttar Pradesh are faced with the challenges of planning a system that incorporates increasing amounts of renewable energy and storage resources, meets rising electricity demand due to economic development and green hydrogen production, and satisfies operational and reliability requirements. To support these various objectives, the National Renewable Energy Laboratory (NREL), RMI, and the Uttar Pradesh New and Renewable Energy Development Agency (UPNEDA) evaluated the least-cost pathways for the state's power sector through 2050. NREL developed a capacity expansion model that identifies investment and operational decisions for every year (2024-2050) for all of India, with detailed representation for the state of Uttar Pradesh, which can provide a framework for recurring planning studies. The purpose of this slide deck is to supplement the main study (published in May 2024) with additional modeling scenarios to explore hydrogen flexibility.

08 HYDROGEN↗

Impacts of Renewable Energy and Green Hydrogen Policies on Uttar Pradesh's Power Sector Future

This report is part of a broader program focused on supporting Indian states with long-term power system planning. More information about this program can be found at the National Renewable Energy Laboratory's "Supporting India's States With Renewable Energy Integration" web page at https://www.nrel.gov/international/india-renewable-energy-integration.html. The power sector in Uttar Pradesh, India's most populous state, is poised to transform over the next few decades due to a combination of national and state-level policies impacting both the supply and demand of electricity. The Government of Uttar Pradesh has policies and plans to develop in-state solar PV, pumped storage hydropower, and green hydrogen. Power system policymakers and utilities in Uttar Pradesh are faced with the challenges of planning a system that incorporates increasing amounts of renewable energy and storage resources, meets rising electricity demand due to economic development and green hydrogen production, and satisfies operational and reliability requirements. To support these various objectives, the National Renewable Energy Laboratory (NREL), RMI, and the Uttar Pradesh New and Renewable Energy Development Agency (UPNEDA) evaluated the least-cost pathways for the state's power sector through 2050. NREL developed a capacity expansion model that identifies investment and operational decisions for every year (2024-2050) for all of India, with detailed representation for the state of Uttar Pradesh, which can provide a framework for recurring planning studies. The main insights from this study can also help inform policy development and investment decisions.

08 HYDROGEN↗

Insights from NREL’s Electrification Futures and LA100 Studies

Electrification of end-use technologies could have important implications for bulk power sector planning, operations, and impacts. By combining previously-defined electrification scenarios with capacity expansion modeling, we evaluate the potential challenges and opportunities associated with electrification. Our scenario analysis reveals that electrification reduces energy consumption and air emissions from across the energy sector, and its impacts on energy system costs are modest due, in part, to the abundance of low-cost resources in the United States.

43 PARTICLE ACCELERATORS↗

Assessing the Economic Value of Underground Thermal Storage for Hybrid Geothermal Power

Solutions are needed to address resource adequacy in the electric power system for highly decarbonized systems. The storage duration, the length of time a storage device can provide continuous output at its rated capacity, must be sufficient to receive full credit toward resource adequacy. Longer peaks and high fractions of variable renewable generation have increased the required duration to potentially seasonal durations. Underground Thermal Energy Storage (UTES) can be adapted to a hybrid storage power plant or heating and cooling applications to satisfy the need for long-duration storage. In this study, we use the Renewable Energy Deployment System (ReEDS) capacity expansion model to evaluate the increase in value for an enhanced geothermal system (EGS) resources by adding UTES. In modeled scenarios, using geothermal without storage as a baseline we compare the increase in economic value for plants with a range of storage characteristics. The added value of a hybrid storage plant changes depending on assumptions including the length of storage duration, efficiency, and ability to charge storage from the grid during periods of low energy prices. Relating proposed characteristics for geothermal UTES hybrids to the modeled economic value provides insight into economically viable costs for developing UTES as well as what combination of technology characteristics and future energy and policy assumptions drive significant value increases.

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Role of Renewable Energy, Storage, and Demand Response in Karnataka's Power Sector Future

Karnataka ranks fourth among Indian states in installed capacity of renewable energy, which accounts for over 50% of its resource mix. The state is positioned to play a leading role in India's energy transition and contribute to meeting national targets for renewable energy thanks, in part, to ambitious state goals to develop Karnataka's abundant zero carbon energy resources and plans to phase out new investments in thermal plants. Power system stakeholders in Karnataka are faced with the challenge of planning a generation portfolio that accounts for the variability of wind and solar resources, meets increasing and shifting electricity demand, and satisfies operational and reliability requirements. The objective of this study is to evaluate least-cost pathways for Karnataka's electric power system through 2050. The capacity expansion model developed for this study identifies power system investment and operational decisions for every year (2020-2050) for all of India, with detailed representation of the state of Karnataka. The study led to five high-level results and provides a framework for recurring planning studies to meet changing system conditions and needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Grid Value of Ocean Current Energy in Florida: Preprint

Ocean current technology has been proposed as a potential contributor to Florida's energy portfolio. There has been limited investigation of how this energy would be valued when integrated into the Florida electrical grid. This study assesses three future grid scenarios to evaluate the impact of adding ocean current to each. NREL's capacity expansion model, Resource Planning Model, is used to identify the least-cost generation mix through 2050, with and without ocean current. The first scenario, Business as Usual, Base case assuming current policies, ocean current does not replace fossil-based technologies. In the second scenario, we allow solar and storage to have lower costs than the first scenario which allows ocean current to retire gas earlier and more variable generation technologies to be deployed. In the third scenario, the Florida carbon constraint 95 by 2050 from 2020 levels case, ocean current can play a bigger role in decarbonization than the two other cases when coupled with other technologies.

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National Transmission Planning Study - Long-Term Modeling Results

The National Transmission Planning Study (NTP Study) analyzed the transformation needed to ensure the U.S. transmission system continues to reliably meet electricity demand as the power sector evolves. The study linked several long- and short-term power systems models to test numerous interregional and regional transmission buildout scenarios. The results included in this dataset are from the long-term capacity expansion modeling, completed with NREL's ReEDS model. This includes nearly 100 future transmission scenarios with a wide range of economic, reliability, and resilience conditions. The dataset includes all the results visualized in the Tableau Public site, as linked below.

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Key Drivers for Offshore Wind Deployment in the Western United States

The western coast of the United States has abundant natural resources, including wind, sun, and water. Despite strong ocean winds, offshore wind energy (OSW) in the Western United States is in the early stages of technology development due largely to the deep water off the coast, which requires floating platforms rather than fixed‐bottom turbines. Floating OSW increases the technical difficulty of installation and thus the cost relative to both fixed‐bottom OSW and land‐based turbines. OSW is a potential generation option to help meet increasing demand on the west coast of the United States because it likely has fewer land‐use conflicts than other technologies and complements sources in the existing electricity supply by providing energy during times of high system stress. This paper examines the possible drivers and barriers to OSW deployment on the West Coast using the National Laboratory of the Rockies' state‐of‐the‐art capacity expansion model and the Regional Energy Deployment System (ReEDS) model. We use ReEDS to explore a multitude of future scenarios looking at key drivers for OSW deployment, including variations on the cost of OSW, electricity demand growth, and the availability of competing technologies to examine the factors that may play a role in OSW growth. Assuming coastal state policies such as renewable portfolio and clean energy standards remain in place, we find that OSW can play a role in meeting electricity demand and provide energy during stressful grid conditions and find that deployment from the least‐cost investment model ranges from 7.6 to 38 GW by 2045.

17 WIND ENERGY↗

Decarbonization and technology cost drivers: considerations for potential future thermoelectric water use in the power sector

The power sector is currently undergoing significant changes, driven by a combination of factors, including decarbonization and technology innovation. This study aims to assess implications of these drivers on U.S. power sector technology futures and the associated water and environmental implications for cooling thermoelectric power plants. Specifically, we evaluate four decarbonization scenarios for the contiguous United States that vary in assumptions concerning demand growth and technology costs, with technology costs driving alternative outcomes that prioritize either technologies that require low amounts of water (such as wind, solar, and battery) or high amounts of water (such as nuclear and carbon capture and storage). These scenarios are executed in a power sector capacity expansion model and compared to two reference scenarios that assume status quo with policy and cost drivers. Our analysis indicates that future U.S. thermoelectric water withdrawals could decrease by 25%–60%, but water consumption could more than triple in some scenarios. These changes are driven by a combination of retirement of some power facilities, shifts in cooling technologies, and new technology deployment. The water use patterns vary across the United States, with the eastern regions demonstrating a lot more variability in water consumption across scenarios than western regions. However, local concerns can influence these possible investments, since increased water consumption can exacerbate water scarcity, leading to conflicts among competing users and affecting regional social, environmental, and economic dynamics. Future work should consider possible costs associated with alternate water sources, as well as improve the representation of water constraints within simulations. Inclusion of extreme events and alternate modeling platforms (e.g. production cost modeling and resource adequacy) may also be warranted to further stress test the robustness of these possible technology futures. Such assessments will be critical for ensuring decarbonization and other infrastructure-oriented investments lead to a reliable and resilient power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A General Method for Estimating Zonal Transmission Interface Limits from Nodal Network Data: Preprint

Capacity expansion models for the electric power system often employ zonal (rather than nodal) resolution, necessitating estimates of aggregate power transfer limits across the interfaces between model zones. Interface limits between planning areas are sometimes published, but they are not generalizable to arbitrary zone shapes. There is thus a need for a reproducible method for estimating interface transfer limits (ITLs) between user-defined zones directly from nodal transmission system data. Here, we present a simple method for estimating ITLs using a DC power flow approximation via the power transfer distribution factor (PTDF) matrix. Linear optimization is performed to identify the distribution of power flows that maximizes the total flow on interface-crossing lines, subject to individual line ratings, limits on bus injection/withdrawal, and the relationships among flows, injections, and withdrawals imposed by the PTDF matrix. We demonstrate the application of the method on a 134-zone ~65000-bus system, and we explore the influence of flow direction, contingency level, and zone size on the estimated ITLs. There is significant heterogeneity in the ratio of the ITL to the sum of interface-crossing line ratings, which highlights the importance of accounting for the physical constraints on power flows imposed by Kirchhoff's laws when estimating zonal ITLs.

17 WIND ENERGY↗

Western Interconnection Baseline Study

The purpose of the baseline study is to evaluate the degree to which current industry planning processes meet the national 2035 decarbonization goals for the Western Interconnection. This analysis serves as a comparative baseline for the scenario analysis conducted in the NTP Study using a Western Interconnection dataset that is readily available to industry. This baseline analysis differs from the production cost modeling analysis and power flow analysis in the main NTP Study report (forthcoming). In particular, the analysis presented in this report reflects a business-as-usual future with an optimistic build out of specific planned transmission projects and foreseeable generation. In contrast, the NTP Study models a future generation and transmission expansion based on optimization from a capacity expansion model. The analysis presented herein also reflects a 2030 timeframe, whereas the main NTP Study production cost modeling analysis and power flow analysis reflect a 2035 time frame. This baseline analysis utilizes industry’s most reliable data to account for future transmission projects across various stages of development, with a particular focus on those in the permitting stage. Additionally, it incorporates projections for changes in generation capacity (both additions and retirements). This baseline analysis outlines a probable trajectory, given current process and practice, for the future of the bulk power system with a horizon extending to 2030.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (MEME-CCS)

This effort employs and adapts an existing, rigorous multiscale electricity modeling platform at the National Renewable Energy Laboratory (NREL) to evaluate carbon capture and sequestration (CCS) and negative emissions technologies (NET) from the ARPA-E FLECCS program. NREL's modeling platform includes the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model, which projects future electricity generation mixes at sub-state-level resolution that are downscaled to the unit-level to enable hourly, zonal or nodal electricity production cost modeling in the PLEXOS model. The resulting hourly price data from PLEXOS is provided to technology developers under the ARPA-E FLECCS program to enable technology-specific economic analysis. The ReEDS-PLEXOS modeling suite is well-established for examining electric sector futures with high renewable energy penetrations, energy storage, electrification, and distributed generation. The key advancement proposed herein utilizes collaboration with CCS experts at the University of Wyoming and the FLECCS teams to create innovative methods for representing CCS and NET in the ReEDS and PLEXOS models. Expanded technology options, new operational parameterizations, and detailed data defining CO2 capture, transportation, and storage systems are being integrated into these models to allow an unprecedented combination of scope and resolution for exploring the future of CCS and NET. The resulting capabilities will take advantage of high-performance computing resources to permit wide-ranging scenario analysis to assess CCS and NET deployment under alternative CO2 prices, fossil fuel prices, electricity demand growth, and other electric sector characteristics. Final outcomes will include publicly available hourly grid operation and price data for any U.S. region of interest along with open-access capacity expansion tools for evaluating CCS/NET systems. These products will help an emerging CCS/NET industry in the United States by providing economics-driven guidance to technology developers while informing policy and investment decisions in the public and private sectors.

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ASEAN Technical Exchange Workshop for System Operators, Regulators, and Policymakers

This presentation provides an in-depth exploration of power system planning, cross-border electricity trading, and battery energy storage systems (BESS), offering actionable insights for system operators, regulators, and policymakers. The first section delves into power system planning and analysis, focusing on capacity expansion models and resource adequacy studies, including their role in optimizing system efficiency, managing emissions, and addressing system reliability risks. Key considerations, such as integration of transmission into generation planning and the forecasting versus optimization of customer distributed energy resources (DER) technologies, are explored. The session highlights critical trade-offs in spatial granularity and model runtimes, as well as the feasibility of aligning distribution investments with capacity expansion efforts. The second section examines cross-border electricity trading, with an emphasis on resource adequacy concepts such as reliability targets, loss of load expectation (LOLE), and planning reserve margins (PRM). Case studies on reserve market design and coordination across US regions provide insights into improving reserve deliverability and managing interregional power balance and congestion. This section also addresses market-to-market congestion management, including advanced strategies for high-voltage direct current (HVDC) optimization and ancillary service delivery. Finally, the presentation covers the rapid evolution of Battery Energy Storage Systems (BESS), highlighting their operational growth, regulatory frameworks, and use cases in grid flexibility, energy storage, and reliability. The discussion focuses on the benefits of BESS for system stability, resilience, and integration of renewable energy, offering insights into its role as a vital component in the transition toward a more sustainable and flexible grid. Key performance parameters, such as throughput, round-trip efficiency, and state of charge, are also examined.

25 ENERGY STORAGE↗

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (MEME-CCS)

This effort employs and adapts a rigorous multiscale electricity modeling platform at the National Renewable Energy Laboratory (NREL) to evaluate carbon capture and sequestration (CCS) and negative emissions technologies (NET) from the ARPA-E FLECCS program. NREL's modeling platform includes the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model, which projects future electricity generation mixes at sub-state-level resolution that are downscaled to the unit-level to enable hourly, zonal or nodal electricity production cost modeling in the PLEXOS model. The ReEDS-PLEXOS modeling suite is well-established for examining electric sector futures with high renewable energy penetrations, energy storage, electrification, and distributed generation. The key advancement proposed herein utilizes collaboration with CCS experts at the University of Wyoming (U.WY) and the FLECCS technology development teams to create innovative methods for representing CCS and NET in the ReEDS and PLEXOS models. Expanded technology options and new operational parameterizations are integrated into these models to allow an unprecedented combination of scope and resolution for exploring the future of CCS and NET. The resulting capabilities permit wide-ranging scenario analysis to assess CCS and NET deployment under alternative scenarios of CO2 prices and competitiveness of flexible CCS and NET technologies. We demonstrate sample deployment and operational outcomes to show how these models are being used to assess the future potential for FLECCS technologies and their impacts on the U.S. electricity system. These products will help an emerging CCS/NET industry in the United States by providing economics-driven guidance to technology developers while informing policy and investment decisions in the public and private sectors.

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County-Level Hourly Renewable Capacity Factor Dataset for the ReEDS Model

This dataset contains hourly capacity factors for each renewable resource class and region (in this case, county). Technologies like large-scale utility PV (UPV), onshore wind, offshore wind, and concentrating solar power (CSP) are included. The dataset contains 7 years of hourly weather data (2007-2013) for different sites across the US and is used as one of the inputs to the ReEDS-2.0 model (see the "ReEDS 2.0 GitHub Repository" resource link below), developed by NREL. The weather profiles apply to any capacity that exists or is built in each region and class. This helps calculate the generation that can be provided using these resources. Open, reference, and limited are 3 scenarios based on land-use allowance, derived from the Renewable Energy Potential (reV) model developed by NREL, which helps generate supply curves for renewable technologies and assess the maximum potential of renewable resources in a designated area. Each zipped file in this dataset corresponds to a technology and contains the respective land-use scenario files required to run that technology in ReEDS. To use this dataset, download and place the extracted files in the locally cloned ReEDS repository inside one of the folders (inputs/variability/multi_year). After completing this copy, upon running the ReEDS model at the county-level spatial resolution for respective analysis purposes, the program will detect the presence of these files and will not fail.

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