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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 OSTI2024

Atlantic Offshore Wind Transmission Study

The Atlantic Offshore Wind Transmission Study (AOSWTS) is part of the U.S. Department of Energy's (DOE) efforts to understand and facilitate the transmission of electricity from wind in the Atlantic Ocean. It was informed by the Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis (Bothwell et al. 2021) and the convening workshops hosted in 2022-2023 by DOE and the U.S. Department of the Interior's Bureau of Ocean Energy Management. The study results help to inform An Action Plan for Offshore Wind Transmission Development in the U.S. Atlantic Region (Baker et al. 2023). DOE's Wind Energy Technologies Office funded AOSWTS. The AOSWTS identifies and evaluates pathways to enable offshore wind energy deployment in the Atlantic Ocean through coordinated offshore transmission solutions in the near term (by 2030) and long term (by 2050). The study fills gaps in prior analyses by providing a multiregional planning perspective that evaluates offshore wind generation development with transmission planning. It incorporates environmental, ocean co-use, and other siting considerations into defining potential offshore transmission routes. The study also compares different multiregional offshore transmission topologies and their associated costs (using potential cable routes) and benefits (in terms of production cost savings and enhanced resource adequacy). In addition, the AOSWTS analyzes reliability impacts from a multiregional perspective. The study provides guidance for policymakers and transmission stakeholders on possible outcomes resulting from a proactive, coordinated, and interregional approach to transmission planning for offshore wind energy development in the Atlantic. While this study presents possibilities, additional work following system operator methods and procedures can help build on this analysis.

17 WIND ENERGY↗

DOE OSTI2024

Atlantic Offshore Wind Transmission Study: Executive Summary

The Atlantic Offshore Wind Transmission Study (AOSWTS) is part of the U.S. Department of Energy's (DOE) efforts to understand and facilitate the transmission of electricity from wind in the Atlantic Ocean. It was informed by the Atlantic Offshore Wind Transmission Literature Review and Gaps Analysis (Bothwell et al. 2021) and the convening workshops hosted in 2022-2023 by DOE and the U.S. Department of the Interior's Bureau of Ocean Energy Management. The study results help to inform An Action Plan for Offshore Wind Transmission Development in the U.S. Atlantic Region (Baker et al. 2023). DOE's Wind Energy Technologies Office funded AOSWTS. The AOSWTS identifies and evaluates pathways to enable offshore wind energy deployment in the Atlantic Ocean through coordinated offshore transmission solutions in the near term (by 2030) and long term (by 2050). The study fills gaps in prior analyses by providing a multiregional planning perspective that evaluates offshore wind generation development with transmission planning. It incorporates environmental, ocean co-use, and other siting considerations into defining potential offshore transmission routes. The study also compares different multiregional offshore transmission topologies and their associated costs (using potential cable routes) and benefits (in terms of production cost savings and enhanced resource adequacy). In addition, the AOSWTS analyzes reliability impacts from a multiregional perspective. The study provides guidance for policymakers and transmission stakeholders on possible outcomes resulting from a proactive, coordinated, and interregional approach to transmission planning for offshore wind energy development in the Atlantic. While this study presents possibilities, additional work following system operator methods and procedures can help build on this analysis.

17 WIND ENERGY↗

DOE OSTI2024

2023 Standard Scenarios Report: A U.S. Electricity Sector Outlook

This report, originally published in December 2023, has been revised in January 2024. There were three changes in the revision. First, Anthony Lopez was added as a contributing author, as he had been erroneously omitted in the original publication. Second, in appendix section A.1 the cost of upgrading a hydrogen combustion turbine from a natural gas turbine was erroneously reported as 20% when it should have been 33%. Lastly, appendix Figure A-8 was erroneously a duplication of the same figure from the Standard Scenarios 2022, it has now been updated to reflect this year’s data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Incorporating Wind Turbine Choice in High-Resolution Geospatial Supply Curve and Capacity Expansion Models

To achieve national decarbonization goals, U.S. annual deployment of wind energy will need to increase by at least fivefold compared to the recent past. Modeling and analysis frameworks can help inform where and how wind energy deployment might occur and thereby help enable the achievement of decarbonization goals. However, most prior wind energy modeling and analysis studies rely on generalized representations of wind energy technologies. Since wind energy technology advancements are expected to increase the competitiveness of wind energy, it is important to incorporate more detailed representations of turbine technology into wind energy modeling. Here we present a new method that incorporates wind turbine choice into the technology representation of land-based wind energy in long-term planning models. Our method integrates three previously published modeling and analysis capabilities: 1) bottom-up cost modeling to estimate future technology costs, 2) geospatial modeling to represent siting decisions, and 3) power sector modeling to evaluate potential deployment. We refer to this approach as a "customized turbine choice" methodology because it creates a composite turbine scenario by choosing from multiple wind turbine technologies—using site-specific optimized turbine layout and selecting the least-cost technology at each location. We demonstrate the capabilities of this new modeling pipeline by examining how the selection of four different wind turbine configurations might evolve from 2021 through 2040. Our results show that using our customized turbine choice methodology could lead to higher estimates for wind future deployment, which indicates that more simplified modeling might underestimate the role that wind energy could play in meeting decarbonization goals. Future research is needed to further explore the implications of turbine choice and to better inform technology researchers, original equipment manufacturers, and other wind industry stakeholders about the market potential of different wind turbine technologies.

17 WIND ENERGY↗