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DOE OSTI2026

Informing Transmission Supply Chain Needs from National Transmission Studies

Recent national studies indicate significant transmission expansion can provide the lowest-cost option to maintain grid reliability while meeting growing demand. However, constraints in domestic supply chains may limit grid expansion across the U.S., with higher costs and longer delays for required transmission equipment. Despite growing evidence of supply chain constraints for transmission components, transmission planning studies often assume transmission equipment is readily available for deployment or analyze future demand using historical trade and manufacturing data that may not capture evolving grid needs. This report aims to address this gap by demonstrating methods to quantify future demand for critical transmission components and input materials from national-scale planning models. These components include power transformers, generator step-up transformers, converter transformers, conductors, circuit breakers, and transmission towers and the materials include aluminum, steel, grain-oriented electrical steel (GOES), and copper. The analytical approach is applied to two nodal transmission expansion scenarios from the National Transmission Planning Study (NTP) to illustrate the methods. These scenarios represent different transmission expansion strategies for the contiguous U.S. to the year 2035: the Alternating Current (AC) scenario includes AC transmission expansion within each interconnection and the Multiterminal (MT) scenario includes interregional transmission expansion across the country using both AC and multiterminal HVDC options between neighboring zones. We also explore potential heuristics to derive transmission component demand from zonal capacity expansion models (CEMs) with coarse representation of the transmission grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Informing Transmission Supply Chain Needs from National Transmission Studies

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

2020 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report summarizes the results of 47 forward-looking 'standard scenarios' of the U.S. power sector simulated by the National Renewable Energy Laboratory (NREL) using the Regional Energy Deployment System (ReEDS) and Distributed Generation (dGen) capacity expansion models. The annual Standard Scenarios, which are now in their sixth year, have been designed to capture a range of possible power system futures considering a variety of factors that impact power sector evolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Deployment Potential of Concentrating Solar Power Technologies in California

As states within the United States respond to future grid development goals, there is a growing demand for reliable and resilient nighttime generation that can be addressed by low-cost, long-duration energy storage solutions. This report studies the potential of including concentrating solar power (CSP) in the technology mix to support California’s goals as defined in Senate Bill 100. A joint agency report study that determined potential pathways to achieve the renewable portfolio standard set by the bill did not include CSP, and our work provides information that could be used as a follow-up. This study uses a capacity expansion model configured to have nodal spatial fidelity in California and balancing-area fidelity in the Western Interconnection outside of California. The authors discovered that by applying current technology cost projections CSP fulfills nearly 15% of the annual load while representing just 6% of total installed capacity in 2045, replacing approximately 30 GWe of wind, solar PV, and standalone batteries compared to a scenario without CSP included. The deployment of CSP in the results is sensitive to the technology’s cost, which highlights the importance of meeting cost targets in 2030 and beyond to enable the technology’s potential contribution to California’s carbon reduction goals.

14 SOLAR ENERGY↗

DOE OSTI2024

Representing Carbon Dioxide Transport and Storage Network Investments within Power System Planning Models

Carbon dioxide (CO 2 ) capture and storage (CCS) is frequently identified as a potential component to achieving a decarbonized power system at least cost; however, power system models frequently lack detailed representation of CO 2 transportation, injection, and storage (CTS) infrastructure. In this paper, we present a novel approach to explicitly represent CO 2 storage potential and CTS infrastructure costs and constraints within a continental-scale power system capacity expansion model. In addition, we evaluate the sensitivity of the results to assumptions about the future costs and performance of CTS components and carbon capture technologies. We find that the quantity of CO 2 captured within the power sector is relatively insensitive to the range of CTS costs explored, suggesting that the cost of CO 2 capture retrofits is a more important driver of CCS implementation than the costs of transportation and storage. Finally, we demonstrate that storage and injection costs account for the predominant share of total costs associated with CTS investment and operation, suggesting that pipeline infrastructure costs have limited influence on the competitiveness of CCS.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Grid Planning Impacts of Hydropower Growth and Decline

Hydropower and pumped storage hydropower (PSH) have a complex and uncertain future in the U.S. electricity system. On one hand, existing assets have the potential for an expanded role in integrating variable renewable energy while new deployment, particularly of PSH, can help meet growing needs for grid flexibility and improved reliability. On the other hand, challenging environmental and cost considerations could limit the extent of new investments in hydropower and PSH capacity and flexibility. This technical presentation demonstrates the use of a high-fidelity capacity expansion model of the U.S. electric grid (the National Renewable Energy Laboratory's Regional Energy Deployment System) to understand the impacts of alternative futures for the hydropower and PSH fleet, including scenarios of both growth and decline. Growth scenarios include new PSH deployment or improved hydropower flexibility, while scenarios of decline reduce the capacity or energy production potential of hydropower and PSH. Economic, environmental, and performance outcomes of the grid are compared across these scenarios to reveal the potential contributions of hydropower and PSH in the U.S. electric sector over the next several decades, focusing on changes to the grid technology mix, electric sector costs, electricity prices, and air emissions. This broad scenario approach demonstrates how flexible hydropower and PSH can help reduce air emissions and cost by complementing variable renewables, but the opposite can occur with reduced hydropower availability, particularly in the next decade. It is important to consider a wide range of scenarios and metrics to gain a national and regional understanding of hydropower's future in the United States.

capacity expansion↗

DOE OSTI2023

Expanded modelling scenarios to understand the role of offshore wind in decarbonizing the United States

An assessment of decarbonization pathways in energy models reveals fundamental limitations in representing factors that are relevant for practical decision-making. Although these modelling limitations are widely acknowledged, their impact on the deployment of individual power generation types is not well understood. As a result, the societal value from such generation types could be vastly misrepresented. Here we explore a wide spectrum of factors that impact offshore wind deployment in the United States using a detailed capacity expansion model. Many factors prescribe a large future role for offshore wind, yet this diverges from what models often show. We extend the typically narrow modelling context through high spatial resolution, several cost and transmission possibilities and various energy-sector policies. Further, we estimate offshore wind to constitute 1-8% (31-256 gigawatts) of total US generation by 2050. This wide range suggests an uncertain but potentially important regional role. Our expansive scenarios demonstrate how to address many limitations of decarbonization modelling.

17 WIND ENERGY↗

DOE OSTI2023

The Role and Value of Interregional Transmission in a Decarbonized U.S. Electricity System

Decarbonizing the U.S. energy system entails a significant expansion of wind and solar power and electrification of end-use applications. Achieving both is more efficient and less costly when interregional transmission capacity is expanded, but the fractured nature of grid planning in the United States is often a barrier to such expansion. Here, we explore the role of interregional transmission under a variety of decarbonization scenarios, using a capacity-expansion model to generate co-optimized portfolios of generation, storage, and transmission that meet decarbonization targets and electrification-driven demand. We explore portfolio and cost differences across 92 scenarios, from scenarios with limited transmission expansion to those that include a meshed high-voltage direct current (HVDC) network. In the core decarbonization scenarios, wind capacity expands by ~10x and solar by ~20x compared to 2020, hundreds of gigawatts of battery storage are deployed, and interregional transmission expands by 3-6x. Transmission expansion occurs nationwide but is concentrated between the central "wind belt" and eastern load centers. The HVDC scenarios result in hundreds of billions of dollars of savings in total system cost, demonstrating the economic benefits of interregional transmission in support of rapid decarbonization.

capacity expansion↗

DOE OSTI2026

Challenges and Opportunities for Electric Utility Modeling and Asset Valuation Frameworks: Case Study on Valuing New Pumped Storage Hydropower

Asset valuation by electric utilities is becoming increasingly difficult in the rapidly changing electric sector. Rapid deployment of variable generation and inverter-based storage systems along with uncertain demand growth, climate, policies, and other factors create a challenging environment for understanding the value proposition of a new potential asset. This report describes an effort between the Tennessee Valley Authority (TVA) and three U.S. Department of Energy laboratories to perform a detailed review of utility modeling and analysis practices for asset valuation and identify challenges and opportunities for advancing its methods into the future. It focuses on a case study of new potential pumped storage hydropower (PSH) because of growing interest in new PSH capacity to provide energy balancing, firm capacity, and a range of ancillary services. Staff from the DOE labs conducted systematic interviews about current practices in capacity expansion modeling, production-cost modeling, hydrological modeling, and transmission stability modeling while also discussing how scenario analysis is conducted and how models and data are integrated. The effort resulted in a set of model, integration, and scenario recommendations that could be valuable to TVA, other utilities, system operators, and other stakeholders conducting integrated grid analysis. Individual model recommendations suggest exploring computational tradeoffs with detail and resolution across spatiotemporal structure, supply- and demand-side details, transmission overlays, market interactions, and ancillary services. Automated processes to pass data between models and conduct larger scenario suites could also enhance valuation practices by enabling a more consistent study of asset value across a broader range of uncertain future grid conditions where PSH could be particularly valuable. TVA and other industry stakeholders can learn from and adapt applied research-grade methods developed by DOE laboratories and other research institutions to improve decision making and accelerate progress towards a reliable, economic, sustainable energy system.

13 HYDRO ENERGY↗

DOE OSTI2022

The Roles and Impacts of PV-Battery Hybrids in a Decarbonized U.S. Electricity Supply

In this paper, we explore the potential impacts of growing industry interest in hybrid systems comprising PV and battery technologies on the results and findings of the Solar Futures Study (DOE 2021). We employ similar scenario definitions in the same ReEDS capacity expansion model, but we perform two versions of each scenario: one in which PV and battery technologies must be deployed separately (No Hybrids), and one in which the model has the option of deploying them together as PVB hybrids (With Hybrids). By comparing the No Hybrids and With Hybrids versions of each scenario, we isolate the impacts of hybridization on the outcomes and findings of the Solar Futures Study. We find that PVB hybrid configurations capture a sizable share of PV deployment, and the highest-net-value PVB hybrid configuration depends strongly on policy conditions. A power sector decarbonization policy generally increases the value proposition of a more forward-looking PVB hybrid configuration that involves significant oversizing of the PV arrays, a larger battery (which facilitates greater recovery and utilization of otherwise clipped energy), and a higher capacity factor. The growing deployment of PVB hybrid configurations primarily displaces standalone PV capacity, such that total installed PV capacity is largely unaffected by the availability of PVB hybrid configurations. However, the higher capacity factors associated with PVB hybrid configurations drive a modest (1-2 percentage point) increase in PV's share of U.S. electricity supply in 2050. Finally, introducing the PVB hybrid configurations influences the future role and makeup of battery storage technologies, and it reduces the required transmission expansion, particularly under scenarios that involve a power sector decarbonization policy.

14 SOLAR ENERGY↗

DOE OSTI2025

Grid Value Analysis of Geothermal Systems for End-Use Applications

Fuel based end-uses for residential, commercial, and industrial consumers require a technology change to achieve economy-wide decarbonization. Space heating accounts for 42% of residential and 32% of commercial energy demand, much of which is currently met through carbon emitting fuels. Industrial energy use is heavily fuel based with electricity currently representing 13% of energy demand. Geothermal heat pumps (GHPs) and geothermal direct use can eliminate the need for CO2 emitting and simultaneously allow for more efficient electrification of end uses. Past work has assessed the impact on total energy costs and generation investments but did not identify specific grid services benefited. Energy usage in residential and commercial structures was assessed by leveraging data from ComStock and ResStock models. These models utilize housing attributes, occupancy patterns, weather data, and sophisticated energy simulations to generate hourly load profiles for individual buildings identified by unique IDs associated with their locations. Industrial sector energy use was evaluated using information from the Manufacturing Energy Consumption Survey (MECS) as well as plant utilization data from the US Census to estimate hourly plant operations. The change in end-use demand for electricity, natural gas, and other fuels was calculated for different technologies that could meet this need. Using the ReEDS capacity expansion model, we produce regional price profiles that capture the grid benefit associated with the amount and timing of energy shifts in the power system from the adoption of geothermal systems relative to other technologies that could meet space heating, space cooling, and process heat requirements. We find that geothermal systems for meeting end-use demand add value to the energy system. In buildings where geothermal systems increase grid costs, these values are offset by reduced fuel costs and benefits to externalities, including emissions and health impacts.

decarbonization↗

DOE OSTI2023

Exploring the Impact of Near-Term Innovations on the Technical Potential of Land-Based Wind Energy

Land based wind may play a critical role in reaching emissions reductions goals and high renewable contribution scenarios with capacity expansion modeling results estimating over 1 terawatt of land-based wind by 2035 to reach 100% clean electricity. Deployment of land-based wind at this magnitude may require significant investments in transmission infrastructure and will require significant land area for new wind and transmission. Cost reductions via technological advancements in wind turbine design, construction, and maintenance will have a major role in enabling the scale of deployment required. Since 1998, the levelized cost of wind energy has fallen by over 60% due to improvements in capacity factors, advancements in turbine controls, and cost reductions in installation, operation, and maintenance. These cost reduction pathways, generally referred to as wind technology "innovations", have enabled significant increases in the capacity and electric generation share of wind power in the United States. Nevertheless, achievements of past wind innovations have not led to widespread wind deployment outside of high wind speed geographies. This study evaluates the potential of near-term innovations to expand the geographic range of economically viable land-based wind power production in the United States. Many challenges to future deployment of wind power can be associated with increasing concentration in high-wind areas. As more wind power is deployed in these same areas, it is likely that residential and regulatory resistance to further deployment will increase, access to transmission will diminish, and options for distant companies and governments with renewable energy goals will remain limited. Therefore, this analysis aims to emphasize the potential for innovations to enable land-based wind in regions with limited wind deployment and with lower wind resource and better access to transmission.

17 WIND ENERGY↗

DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗

DOE OSTI2021

Evaluating the Interactions Between Variable Renewable Energy and Diurnal Storage

Cost declines and growing deployment of photovoltaic (PV), wind, and storage have led to increasing interest in the potential interactions of these three technologies as their role in the power system grows. In this work we enhance a national-scale capacity expansion model to evaluate how PV, wind, and storage interact in the evolution of the power system. Importantly, the modeling framework captures interactions in both investments and operations. Through this work we identify significant synergies between PV and storage. Scenarios with more PV always have more storage, and scenarios with more storage always have more PV. This synergy is due to the diurnal alignment of PV generation with 4-8 hour storage, and to the ability of PV to narrow system peaks to allow shorter-duration storage to serve as a peaking resource. Interactions between wind and storage are less pronounced, though we do observe that longer-duration storage resources appear to provide greater value for wind.

14 SOLAR ENERGY↗

DOE OSTI2022

Retail Rate Projections for Long-Term Electricity System Models

Electricity prices reported in most electricity-system planning studies leave out many price components and do not translate into retail rates, making it difficult to interpret how projected electricity system changes will impact costs to consumers. Full transmission costs are left out of many studies; distribution and administration costs are similarly excluded or highly simplified. Here, we present a detailed bottom-up accounting method for projecting future retail electricity rates in the United States. Making the simplifying assumption that each state is served by an investor-owned utility (IOU), we translate projected generation and transmission capacity and costs from the Regional Energy Deployment System (ReEDS) capacity-expansion model into IOU balance sheet expenditures, accounting for depreciation, taxes, and the breakdown between operating and capitalized (rate-based) expenses. Distribution, administration, and intra-regional transmission costs are projected forward based on empirical trends over the past decade. Modeled bottom-up electricity rates are compared to historical rates from 2010-2019, and the sensitivity of modeled rates to a range of financing and modeling assumptions is explored. Distribution and administration rate components account for roughly 40% (4.4 ¢/kWh) of the projected national-average retail rate over 2020-2050 under central assumptions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Exploring the cost implications of increased renewable energy for the U.S. power system

Not Available

Cole, Wesley (ORCID:000000029194065X)↗

DOE OSTI2023

Variability in Diurnal and Seasonal Ambient Conditions on Geothermal Plant Performance and Cost

Geothermal plant performance is bounded by the second law efficiency, which accounts for the quantity of exergy that can be converted into useful work. This, in turn, is dependent on the geothermal resource temperature and the temperature of the heat sink (i.e., the ambient temperature). In this study, we show that ambient temperature variability on a diurnal and seasonal basis can affect performance and cost estimations for geothermal plants. We have utilized the updated System Advisor Model (SAM) to assess nine geothermal sites with existing resource capacities across three climate zones. Our analysis shows that both evaporatively-cooled flash and air-cooled binary cycle plants are affected by temperature, with a slightly higher effect in enhanced geothermal system binary sites. By assuming an ambient (wet bulb) temperature baseline of 15.6 degrees C (60 degrees F) and comparing baseline results to those from site-specific data, we observe up to 15% underestimation of plant performance and up to 20% overestimation of cost. These results make a case for the inclusion of location-based weather data as inputs to supply curves that are used in capacity expansion models for the prediction of future geothermal deployment scenarios.

ambient temperature↗

DOE OSTI2022

Understanding Economic and Deployment Benefits of Wind-PV Hybrid Power Plants

The least-cost approach to decarbonizing the U.S. electricity supply will likely involve a significantly expanded share of variable renewable energy (VRE) generation. Many strategies and approaches have been identified to address integration challenges in a VRE-dominated system, including standalone and coupled battery systems. In this study, we explored the current and future potential of utility-scale hybrid energy systems comprising PV, wind, and lithium-ion battery technologies (PV-wind-battery systems). Analysis results include temporal complementarity of wind and PV resources across the contiguous United States, with an emphasis on metrics that quantify reductions in variability that can be achieved through hybridization. We further use a price-taker model with simulated hourly energy and capacity prices to determine the revenue-maximizing dispatch of a range of PV-wind-battery configurations across Texas, from the present through 2050. We find 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. Finally, capacity expansion modeling of PV-wind systems indicates that hybridization can reduce transmission expansion requirements associated with a heavily decarbonized U.S. electricity system.

complementarity↗