2025 ATB Approach and Methodology
The 2025 Electricity Annual Technology Baseline (ATB) presents the cost and performance of typical electricity generation plants in the United States. It represents electricity generation plants by either 1) reflecting the entire geographic range of the resource with a few points averaging similar characteristics or 2) providing examples to demonstrate a range associated with resource potential. Foundational to this averaging approach, the National Laboratory of the Rockies (NLR) uses high-resolution, location-specific resource data to represent site-specific capital investment and estimated annual energy production for all potential renewable energy plants in the United States.
For all technologies in the ATB except biopower, the ATB data and website include the following:
- Base Year estimates for parameters that include primary cost and performance metrics:
- Capital expenditures (CAPEX)
- Operating expenditures (OPEX)
- Three scenarios for future technology innovation and their associated parameter values
- The 2025 ATB includes a pilot of an Expanded Cost Drivers Case with three additional scenarios for a limited set of technologies.
- Descriptions of the resource, cost and performance estimation methodology, and data sources.
Renewable technologies and Nuclear also include Capacity factor.
Nuclear data also include ramp rates.
For fossil (natural gas and coal) generation plants, the ATB data and website also include the following:
- Operating range (expected availability; minimum emissions-compliant load)
- Full load design emissions rates for carbon dioxide (CO2), nitrogen oxides, sulfur dioxide, particulate matter, and mercury.
For biopower plants, the ATB:
- Relies on Energy Information Administration (EIA) representation of future plant cost estimates through 2050 from the Annual Energy Outlook (AEO) 2025 (EIA, 2025)
- Represents the average biopower feedstock price based on the U.S. Billion Ton Update study (DOE, 2011) through 2030
- Holds the biopower feedstock price at 2030 levels through 2060.
Base Year (2023) Costs in the ATB
Base Year (2023) costs in the 2025 ATB are from the sources in the following table.
| Technology | Source |
|---|---|
| Land-based wind power plants | CAPEX in the Base Year is associated with the 2023 market average turbine. The Base Year value for each wind speed class depends on the selected representative technology (Stehly et al., 2024). The all-in OPEX (operations and maintenance [O&M]) cost also corresponds to the market average turbine (Stehly et al., 2024). |
| Offshore wind power plants | Base Year costs are estimated with a combination of NLR's bottom-up cost models for gigawatt-scale commercial fixed-bottom projects and demonstration-scale (<100-megawatt [MW]) floating projects, though we present floating costs in 2030 and beyond only when the first gigawatt-scale projects could feasibly be built in the United States. Specifically, the Renewable Energy Potential Model (reV) and NLR Wind Analysis Library (NRWAL) are used to assess offshore wind plant costs across U.S. waters as a function of site-specific parameters including wind resource, water depth, and distances to critical infrastructure (Maclaurin et al., 2019); (Nunemaker et al., 2023). Those site-specific cost estimates are informed by the Offshore Renewables Balance of System and Installation Tool (ORBIT) for CAPEX, the Windfarm Operations and Maintenance cost-Benefit Analysis Tool (WOMBAT) for OPEX, and the FLOw Redirection and Induction in Steady State (FLORIS) tool for American Electric Power (AEP) (Nunemaker et al., 2020); (Hammond and Cooperman, 2022); (National Renewable Energy Laboratory (NREL), 2021). ATB cost estimates are spatial averages presented in terms of wind classes by binning the sites on cost and hub-height wind speed. |
| Distributed wind power projects | The 2024 ATB projection of Moderate Scenario CAPEX in 2023 is inflated to 2023 dollars and used as a base year estimate in the 2025 ATB. These cost estimates were initially informed by NLR's 2022 Cost of Wind Energy study (Stehly et al., 2023) and the Distributed Wind Energy Futures Study (McCabe et al., 2022). The all-in O&M costs in the Base Year for all four project scales correspond to O&M in the 2022 Cost of Wind Energy Review, with adjustments for inflation (Stehly et al., 2023). |
| Utility, commercial, and residential photovoltaic (PV) plants | CAPEX for 2023 is based on bottom-up cost modeling and market data from (Ramasamy et al., 2023). O&M costs are based on modeled pricing for PV systems (Ramasamy et al., 2023). |
| Concentrating solar power (CSP) plants | CAPEX for 2022 is for a representative power tower with 10 hours of storage and a solar multiple of 2.4. This is based on recent assessment of the industry in 2022 and updated CSP system costs, including a bottom-up CSP cost analysis for heliostat components, available in Version 2024.12.12 of the System Advisor Model (SAM) (Turchi et al., 2019); (Kurup et al., 2022). |
| Geothermal plants | Overnight capital cost and O&M costs are from bottom-up cost modeling using the Geothermal Electricity Technology Evaluation Model (GETEM) and inputs from the GeoVision Business-as-Usual scenario (DOE, 2019); (Augustine et al., 2019). Updated 2023 Base Year cost assumptions are based on advanced drilling and productive reservoir creation successes in ongoing enhanced geothermal system (EGS) demonstration and commercial projects (Xing et al., 2024); (Norbeck et al., 2024); (Akindipe and Witter, 2025) and industry stakeholder consultations (Akindipe et al., 2024). |
| Hydropower plants | Nonpowered dam (NPD) data are based on a reduced-form model estimated using data from a 2020 cost analysis (Oladosu et al., 2021); (Oladosu and Ma, 2024). New stream-reach development (NSD) data are retained from previous years and are based on the Hydropower Vision study (DOE, 2016), with bottom-up cost modeling from the Hydropower Baseline Cost Modeling report (O'Connor et al., 2015). |
| Utility-scale PV-plus-battery | CAPEX assumptions for utility-scale PV-plus-battery are based on new bottom-up cost modeling and market data from (Ramasamy et al., 2023), (DOE, 2024), and (Cole et al., 2025) and reflect a 100-megawatts alternating current (MWAC) utility-scale PV-plus-battery system comprising 132-megawatts direct current (MWDC) one-axis tracking PV coupled with 78-MWDC battery storage with 4-hour duration. O&M costs are based on modeled pricing and include a full battery replacement after 15 years of operation. When accounting for state-of-charge and round-trip efficiency constraints, the usable stored energy for the battery component is roughly half the inverter capacity, which is consistent with common relative battery sizing in recent and proposed utility-scale PV-plus-battery projects (Bolinger et al., 2023). Capacity factors and tax credits assume 75% of the energy used to charge the battery component is derived from the coupled PV (on an annual basis). |
| Utility-scale, commercial, and residential battery storage | 2023 costs for utility-scale battery energy storage systems (BESS) are based on a bottom-up cost model using the data and methodology for utility-scale BESS in (Cole et al., 2025). Commercial and residential systems use the same data and methodology, with sector-specific inputs replacing utility-scale inputs as appropriate. |
| Pumped storage hydropower (PSH) plants | Resource characterizations are from a national closed-loop PSH resource assessment documented by (Rosenlieb et al., 2022), and subsequent updates are described in "Closed-Loop Pumped Storage Hydropower Supply Curves" (NLR). Capital costs are estimated using the NLR bottom-up PSH cost model (Cohen et al., 2023) with updates from (Rosenlieb et al., 2026), and O&M costs are from (Mongird et al., 2020). |
| Natural gas and coal | Estimates of performance and costs for available fossil-fueled electricity generating technologies are representative of current commercial offerings and/or projects that began commercial service within the past 10 years for both new plants and retrofits (Schmitt et al., 2022), (Buchheit et al., 2023), (Schmitt and Homsy, 2023), and (Turner et al., 2025). |
| Nuclear | CAPEX and O&M for 2023 are based on the following:
|
| Biopower | These costs are based on the Annual Energy Outlook (EIA, 2025) reported costs. Because the projections in the Annual Energy Outlook typically begin 2 years after the ATB Base Year, costs for the missing years (including the Base Year) are backward-extrapolated from the Annual Energy Outlook projection. |
Future Cost Projections
The ATB future projections are based primarily on expert analysis, bottom-up modeling, and literature on specific technology innovations, which are described in detail for each technology. The categories of innovations for each technology are shown in the following table. The innovations listed in the technology innovation table on each technology page, and summarized here, represent innovations assumed to drive most of the cost reductions in the ATB scenarios. These lists do not include all potential innovations, and they include only innovations that directly impact cost and performance.
| Land-Based Wind |
|
| Offshore Wind |
* Effects from plant economies of scale included only for floating offshore wind because the technology is nascent and the learning curve methodology captures cost reduction effects of the technology maturing over time with increasing deployment. We present floating offshore wind cost estimates in 2030 and beyond only when the first gigawatt-scale projects could feasibly come online in the United States. All operational floating capacity exists at pilot- and demonstration-scale projects only (<100 MW) (Equinor, 2023). Fixed-bottom cost estimates are reflective of gigawatt-scale commercial projects in all years. |
| Distributed Wind |
|
| Solar Photovoltaics |
|
| Concentrating Solar Power |
|
| Geothermal |
|
| Hydropower |
|
| Utility-Scale PV-Plus-Battery | See the Solar Photovoltaics and Battery Storage rows above and below, respectively, in this table. |
| Battery Storage |
|
| Pumped Storage Hydropower |
|
| Natural Gas and Coal |
|
| Nuclear |
|
References
The following references are specific to this page; for all references in this ATB, see References.
Abou-Jaoude, Abdalla, Levi Larsen, Nahuel Guaita, Ishita Trivedi, Frederick Josek, Christopher Lohse, Edward Hoffman, Nicolas Stauff, Koroush Shirvan, and Adam Stein. “Meta-Analysis of Advanced Nuclear Reactor Cost Estimations.” Idaho National Laboratory, June 2024. https://www.osti.gov/biblio/2371533.
Akindipe, Dayo, and Erik Witter. “2025 Geothermal Drilling Cost Curves Update.” In Proceedings, 50th Workshop on Geothermal Reservoir Engineering. Stanford University, Stanford, California: Stanford University, 2025. https://pangea.stanford.edu/ERE/db/GeoConf/papers/SGW/2025/Akindipe.pdf.
Akindipe, Dayo, Erik Witter, Matthew Prilliman, Brian Mirletz, Jonathan Ho, Whitney Trainor-Guitton, Paul Pinchuk, and Travis Williams. “Geothermal Power Systems Analysis: Outcome of Industry Stakeholders Workshop: Preprint.” GRC Transactions 48 (2024): 607–18. https://docs.nlr.gov/docs/fy25osti/90784.pdf.
Al-Dawood, Khaldoon, Botros Hanna, Sai Balla, Rodrigo de Oliveira, Samuel Garcia, Dan McCarthy, Chandrakanth Bolisetti, Ben Lindley, and Abdalla Abou-Jaoude. “Open-Source Microreactor Design Models for Technoeconomic Assessment.” SSRN Scholarly Paper. Rochester, NY: Social Science Research Network, March 3, 2025. https://doi.org/10.2139/ssrn.5163464.
Augustine, Chad, Jonathan Ho, and Nate Blair. “GeoVision Analysis Supporting Task Force Report: Electric Sector Potential to Penetration.” Golden, CO: National Renewable Energy Laboratory, 2019. https://doi.org/10.2172/1524768.
Bolinger, Mark, Will Gorman, and Joseph Rand. “Hybrid Power Plants: Status of Operating and Proposed Plants, 2023 Edition.” Berkeley, CA: Lawrence Berkeley National Laboratory, August 10, 2023. https://escholarship.org/content/qt65f1013r/qt65f1013r.pdf.
Buchheit, Kyle L., Alex Zoelle, Eric Lewis, Marc Turner, Tommy Schmitt, Norma Kuehn, Sally Homsy, et al. “Eliminating the Derate of Carbon Capture Retrofits - Revision 2.” National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States), March 31, 2023. https://doi.org/10.2172/1968037.
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McCabe, Kevin, Ashreeta Prasanna, Jane Lockshin, Parangat Bhaskar, Thomas Bowen, Ruth Baranowski, Ben Sigrin, and Eric Lantz. “Distributed Wind Energy Futures Study.” Golden, CO: National Renewable Energy Laboratory, May 2022. https://doi.org/10.2172/1868329.
Mongird, Kendall, Vilayanur Viswanathan, Jan Alam, Charlie Vartanian, Vincent Sprenkle, and Richard Baxter. “2020 Grid Energy Storage Technology Cost and Performance Assessment.” Washington, D.C.: U.S. Department of Energy, December 2020. https://www.energy.gov/energy-storage-grand-challenge/downloads/2020-grid-energy-storage-technology-cost-and-performance.
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