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Changes in 2023

The Electricity 2023 ATB provides a transparent set of technology cost and performance data for electric sector analysis. The update of the 2022 ATB to the 2023 ATB includes general updates to all technologies as well as technology-specific updates—both of which are described on this page. Use the following charts to explore the changes from 2022 to 2023.

Parameter value projections by ATB projection year

Compare the 2022 ATB and the 2023 ATB. Click on the black arrow to the right of "click arrow to explore details" to select a parameter (LCOECAPEX, fixed operation and maintenance O&M [FOM], capacity factor, and fixed charge rate [FCR]) and other filters.

General Updates to All Technologies

  • The financial assumptions are updated to reflect increases in interest rates and the cost of capital.
  • The Market + Policies case are updated to reflect the tax credits in the Inflation Reduction Act of 2022.
  • The Base Year is updated from 2020 to 2021 using new market data or analysis where applicable.
  • The dollar year is updated from 2020 to 2021 with a 4.7% inflation rate (BLS, forthcoming).
  • Historical data are updated to include data reported through year end 2021.

Generation Updates Summary

  • Land-Based Wind: Wind turbine technology configurations are now developed separately from cost and performance assumptions, which allows for multiple technologies to be used within each scenario. The scenarios are defined by combining bottom-up engineering-based modeling to inform the Moderate Scenario with calculated learning rates used to inform the Conservative and Advanced scenarios. Wind turbine technology configuration is now wind speed class-specific and is selected by the technology configuration with the lowest LCOE within each wind speed class. 
  • Offshore Wind: The same experiential learning methodology as 2021 is used to derive future cost reductions. Empirical market data are updated, leading to a lower CAPEX learning rate of 7.2%. Future global deployment projections are increased for both fixed-bottom and floating offshore wind.
  • Distributed Wind: This technology was added 2022 ATB for the first time, and there are no major updates in the 2023 ATB.
  • Photovoltaics: Initial cost metrics are informed by new benchmark results from (Ramasamy et al., 2021), and projections are based on (Ramasamy et al., 2022). Utility-scale capacity factor numbers now assume bifacial panels.
  • Concentrating Solar Power: Component and system cost estimates for the Base Year now include data from recent heliostat bottom-up analysis (Kurup et al., 2022). There have been updates to the defaults in the System Advisor Model (SAM) power tower molten salt physical model.
  • Geothermal: Near-field and deep enhanced geothermal system (EGS) plant costs are fully distinguished. A single-factor learning curve is applied to future projections in the Moderate and Advanced scenarios.
  • Hydropower: No changes are made from 2021 data.
  • Utility-Scale PV-Plus-Battery: See Photovoltaics and Battery Storage.
  • Battery Storage: Base year CAPEX is updated consistent with new benchmark results in (Ramasamy et al., 2022). Projections are revised based on a new literature survey (Cole and Karmakar, 2023).
  • Pumped Storage Hydropower: Capital costs and resource characteristics are updated, with changes relative to (Rosenlieb et al., 2022) described in "Closed-Loop Pumped Storage Hydropower Supply Curves" (NREL).
  • Natural Gas and Coal: The 2023 ATB adds retrofit cases for natural gas and coal technologies. The trajectory for Natural Gas Fuel Cells has been provided independently of combined cycle plants. Learning rates are updated to reflect (EIA, 2023)

Technology-Specific Updates

Land-Based Wind

  • Base Year: Capital expenditures Capital expenditures (CAPEX) associated with the four representative technologies are estimated using bottom-up engineering models for hypothetical wind plants installed in 2021. The Base Year value for each wind speed class is dependent on the selected representative technology. The all-in operating expenditure cost for each representative technology is informed by recent literature (Liu and Garcia da Fonseca, 2021) and varies by the representative wind turbine's rating. Capacity factors are calculated by generating a power curve for each representative wind turbine technology using the Weibull distribution and the average annual wind speed in the wind speed class in which the representative wind turbine is placed. 
  • Projections: The technology configurations are used to estimate the total system CAPEX of a theoretical commercial scale (e.g., 200-MW) project and changes for each of the scenarios (i.e., Conservative, Moderate, and Advanced) from bottom-up engineering models and assumed learning rates. Operating expenditure estimates vary by wind turbine rating (Liu and Garcia da Fonseca, 2021) and change for each scenario based on assumed learning rates. Net cash flow projection methods are similar to the base year but assume technology innovations that increase wind plant energy capture through advanced controls and reduce total system losses for each scenario. 

Offshore Wind

  • Base Year: As in the 2022 ATB, CAPEX and O&M costs are calculated with a combination of bottom-up techno-economic cost modeling (Beiter et al., 2016) and experiential learning effects with economies of size and scale from higher turbine and plant ratings (Beiter et al., 2020)(Shields et al., 2022). Capacity factors are determined using a representative power curve for a generic National Renewable Energy Laboratory (NREL)-modeled 6-MW offshore wind turbine and updated in the 2023 ATB based on innovation trajectories from (Beiter et al., 2016) to reflect the 8-MW turbine technology assumed to be available starting in 2021. These capacity factors include geospatial estimates of gross capacity factors for the entire national wind resource (Musial et al., 2016).
  • Projections: For the 2023 ATB, the CAPEX cost reduction trajectories use the same experiential learning curves derived in the 2022 ATB. As the learning curves predict future costs as a function of future offshore wind deployment, future costs in each of the ATB technology innovation scenarios are driven by different levels of deployment based on updated literature estimates.

Distributed Wind

Photovoltaics (PV): Utility-Scale, Commercial, and Residential

  • Base Year: CAPEX for plants with a commercial operation date of 2021 are based on bottom-up modeling and market data from (Ramasamy et al., 2021), the same source as the 2022 ATB. For 2022 commercial operation date CAPEX, the new data are from (Ramasamy et al., 2022). The O&M costs are based on modeled pricing for PV systems from those same references.
  • Projections: The DC-to-AC ratio (or inverter loading ratio) for utility-scale PV is changed from 1.28 in the 2022 ATB to 1.34 in the 2023 ATB for the base year and future years. The straight-line improvements in cost metrics through 2035 are now calculated using the 2022 benchmarks from (Ramasamy et al., 2022) as the initial points.

Concentrating Solar Power (CSP)

  • Base Year:  Based on a recent assessment of the industry, bottom-up cost model, and initial supply chain analysis (Turchi et al., 2019) (Kurup et al., 2022), CSP costs in the 2023 ATB are based on cost estimates for CSP components that are available in Version 2021.12.02 of the System Advisor Model (SAM). As in the 2022 ATB, future year projections are informed by the literature, NREL expertise, and technology pathway assessments for reductions in CAPEX. 
    • The SAM Version 2021.12.02 has had default updates, including an update in the power cycle calculations to fix an error. The solar radiation database (NSRDB) has been updated with new resource data. The heliostat field design point was changed from 99% to 95% based on findings from the HelioCon Roadmap (Zhu et al., 2022). After these changes were implemented, the SAM optimization routines were run. The SAM CSP molten salt power tower heliostat field size and the power tower height have increased due to the re-optimization.
  • Projections: As in the 2022 ATB, the Moderate Scenario assumes a transition to a supercritical CO2 cycle in the powerblock, advanced coatings on the receiver, improved tanks, pumps, and component configurations for the thermal storage unit, and improved heliostat installation and learning that are due to deployment in the solar field. The Advanced Scenario assumes higher-temperature supercritical CO2 ; a higher-temperature receiver; advanced storage compatible with higher temperatures; and low-cost, modular solar fields with increased efficiency.

Geothermal

  • Base Year: As in the 2022 ATB, the O&M derived from the Geothermal Electricity Technology Evaluation Model (GETEM) are decreased by 23% based on proprietary geothermal industry data. A reduction in plant contingency (from 15% to 10%) results in lower CAPEX for most technologies except hydrothermal binary. The significantly lower CAPEX for EGS technologies, compared to the 2022 ATB, are due to revisions in the model assumptions for exploration drilling. As in the 2022 ATB, estimates are based on bottom-up cost modeling using the GETEM and inputs from the GeoVision Business-as-Usual scenario (DOE, 2019). The Base Year is updated to the 2021$ dollar year based on the consumer price index and producer price indices.
  • Projections: A technology-agnostic cost multiplier is applied to 2021 overnight capital costs to estimate 2022 costs. This consumer price index-based cost multiplier accounts for an expected increase in 2022 costs due to a significant rise in inflation and interest rates. Future CAPEX projections between 2022 and 2035 for the Moderate and Advanced scenarios are based on a single-factor learning curve (Fukui et al., 2017). The learning rates used to obtain the curves are 13% for hydrothermal and 18% for EGS Moderate Scenarios and 30% for all Advanced Scenarios (Fukui et al., 2017)(Latimer and Meier, 2017). After 2035, a 0.5% annual reduction is applied to the CAPEX up to 2050. The 2035 CAPEX for the Advanced Scenario is largely based on the Technology Improvement scenario assumptions from the GeoVision Study (DOE, 2019)(Augustine et al., 2019)), but includes some updates on well injectivity/productivity (Snyder et al., 2017). The 2035 Moderate Scenario CAPEX is based on the Intermediate 1 Drilling Curve detailed as part of the GeoVision with improvements in stimulation success and well injectivity/productivity. The Conservative Scenario assumes a 0.5% annual reduction in CAPEX from 2022 to 2050 as implemented in the AEO2015 (EIA, 2015).

Hydropower

  • Base Year: The non-powered dam (NPD) data in the 2023 ATB are estimates of costs from a reduced-form model estimated with bottom-up simulation results for nearly 20 reference sites (Oladosu et al., 2021). Data for New stream-reach development (NSD) in the 2023 ATB are retained from previous years based on projections developed for the Hydropower Vision study (DOE, 2016) using technological learning assumptions and bottom-up analysis of process and/or technology improvements to provide a range of future cost outcomes (O'Connor et al., 2015).
  • Projections: The near-term innovation case for NPD is judged to be applicable in the next 5–10 years and includes the use of new materials for penstocks and matrix turbines to reduce the cost of civil works (Oladosu et al., 2021). The NSD projections use a mix of the U.S. Energy Information Administration's technological learning assumptions, input from a technical team of Oak Ridge National Laboratory researchers, and the experience of expert hydropower consultants.

Utility-Scale PV-Plus-Battery

  • Base Year: CAPEX for plants with a commercial operation date of 2022 is based on new bottom-up modeling and 2022 Q1 market data from (Ramasamy et al., 2022). Cost savings for colocated systems have also been updated using that report. O&M costs now include the full replacement of the battery in year 15, in contrast with the augmentation schedule in the 2022 ATB.
  • Projections: As in the 2022 ATB, PV-plus-battery projections in the 2023 ATB are driven primarily by CAPEX cost improvements but also by improvements in energy yield, operating cost, and cost of capital (for the Market + Policies case). Projected technology costs are based on a new report (Ramasamy et al., 2022) .

Battery Storage

  • Base Year: CAPEX is based on new bottom-up modeling and market data from a new report (Ramasamy et al., 2022).
  • Projections: Updated cost projections are based on a literature survey as described by (Cole and Karmakar, 2023). This literature survey incorporates projections that show near-term increases in price, as well as those that project rapid price declines.

Pumped Storage Hydropower (PSH)

Natural Gas and Coal

  • Base Year: Base year cost and performance data are now based on the same source as carbon capture and sequestration performance data, (Schmitt et al., 2022).
  • Projections: Projections in the 2023 ATB are based on the rate of cost improvement from the AEO2023 (EIA, 2023). Natural Gas Fuel Cell technologies are represented as a discrete technology trajectory.

Nuclear and Biopower

  • Base Year and Projections: Cost and performance estimates are updated to match the AEO2023 Reference scenario (EIA, 2023).

References

The following references are specific to this page; for all references in this ATB, see References.

BLS. “CPI for All Urban Consumers (CPI-U).” U.S. Bureau of Labor Statistics, n.d. https://beta.bls.gov/dataViewer/view/timeseries/CUSR0000SA0.

Ramasamy, Vignesh, David Feldman, Jal Desai, and Robert Margolis. “U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks: Q1 2021.” Golden, CO: National Renewable Energy Laboratory, 2021. https://doi.org/10.2172/1829460.

Ramasamy, Vignesh, Jarett Zuboy, Eric O’Shaughnessy, David Feldman, Jal Desai, Michael Woodhouse, Paul Basore, and Robert Margolis. “U.S. Solar Photovoltaic System and Energy Storage Cost Benchmarks, With Minimum Sustainable Price Analysis: Q1 2022.” Golden, CO: National Renewable Energy Laboratory, 2022. https://doi.org/10.2172/1891204.

Kurup, Parthiv, Sertac Akar, Stephen Glynn, Chad Augustine, and Patrick Davenport. “Cost Update: Commercial and Advanced Heliostat Collectors.” Golden, CO: National Renewable Energy Laboratory, 2022. https://doi.org/10.2172/1847876.

Cole, Wesley, and Akash Karmakar. “Cost Projections for Utility-Scale Battery Storage: 2023 Update.” Golden, CO: National Renewable Energy Laboratory, 2023. https://www.nrel.gov/docs/fy23osti/85332.pdf.

Rosenlieb, Evan, Donna Heimiller, and Stuart Cohen. “Closed-Loop Pumped Storage Hydropower Resource Assessment for the United States.” Golden, CO: National Renewable Energy Laboratory, 2022. https://doi.org/10.2172/1870821.

EIA. “Annual Energy Outlook 2023.” Washington, D.C.: U.S. Energy Information Administration, March 2023. https://www.eia.gov/outlooks/aeo/.

Liu, Daniel, and Leila Garcia da Fonseca. “2021 O&M Economics and Cost Data for Onshore Wind Power Markets.” Wood Mackenzie, May 2021. https://www.woodmac.com/reports/power-markets-oandm-economics-and-cost-data-for-onshore-wind-power-markets-2021-497998/.

Beiter, Philipp, Walter Musial, Aaron Smith, Levi Kilcher, Rick Damiani, Michael Maness, Senu Sirnivas, et al. “A Spatial-Economic Cost-Reduction Pathway Analysis for U.S. Offshore Wind Energy Development from 2015-2030.” Golden, CO: National Renewable Energy Laboratory, 2016. https://doi.org/10.2172/1324526.

Beiter, Philipp, Walt Musial, Patrick Duffy, Aubryn Cooperman, Matt Shields, Donna Heimiller, and Mike Optis. “The Cost of Floating Offshore Wind Energy in California between 2019 and 2032.” Golden, CO: National Renewable Energy Laboratory, November 2020. https://doi.org/10.2172/1710181.

Shields, Matt, Philipp Beiter, and Jake Nunemaker. “A Systematic Framework for Projecting the Future Cost of Offshore Wind Energy.” Golden, CO: National Renewable Energy Laboratory, 2022. https://doi.org/10.2172/1902302.

Musial, Walt, Donna Heimiller, Philipp Beiter, George Scott, and Caroline Draxl. “2016 Offshore Wind Energy Resource Assessment for the United States.” Golden, CO: National Renewable Energy Laboratory, September 2016. https://doi.org/10.2172/1324533.

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.

Stehly, Tyler, and Patrick Duffy. “2020 Cost of Wind Energy Review.” Golden, CO: National Renewable Energy Laboratory, January 2022. https://www.nrel.gov/docs/fy22osti/81209.pdf.

Lantz, Eric, Benjamin Sigrin, Michael Gleason, Robert Preus, and Ian Baring-Gould. “Assessing the Future of Distributed Wind: Opportunities for Behind-the-Meter Projects.” Golden, CO: National Renewable Energy Laboratory, November 1, 2016. https://doi.org/10.2172/1333625.

DOE. “Wind Vision: A New Era for Wind Power in the United States.” Washington, D.C.: U.S. Department of Energy, 2015. https://doi.org/10.2172/1220428.

Turchi, Craig, Matthew Boyd, Devon Kesseli, Parthiv Kurup, Mark Mehos, Ty Neises, Prashant Sharan, Michael Wagner, and Timothy Wendelin. “CSP Systems Analysis: Final Project Report.” Golden, CO: National Renewable Energy Laboratory, May 2019. https://doi.org/10.2172/1513197.

Zhu, Guangdong, Chad Augustine, Rebecca Mitchell, Matthew Muller, Parthiv Kurup, Alexander Zolan, Shashank Yellapantula, et al. “Roadmap to Advance Heliostat Technologies for Concentrating Solar-Thermal Power.” Golden, CO: National Renewable Energy Laboratory, 2022. https://doi.org/10.2172/1888029.

DOE. “GeoVision: Harnessing the Heat Beneath Our Feet.” Washington, D.C.: U.S. Department of Energy, May 2019. https://doi.org/10.15121/1572361.

Fukui, Rokuhei, Carl Greenfield, Katie Pogue, and Bob van der Zwaan. “Experience Curve for Natural Gas Production by Hydraulic Fracturing.” Energy Policy 105, no. June 2017 (June 1, 2017): 263–68. https://doi.org/10.1016/j.enpol.2017.02.027.

Latimer, Tim, and Peter Meier. “Use of the Experience Curve to Understand Economics for At-Scale EGS Projects.” Stanford, CA: Stanford University, February 15, 2017. https://pangea.stanford.edu/ERE/pdf/IGAstandard/SGW/2017/Latimer.pdf.

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.

Snyder, Diana M., Koenraad J. Beckers, Katherine R. Young, and Henry Johnston. “Analysis of Geothermal Reservoir and Well Operational Conditions Using Monthly Production Reports from Nevada and California.” Davis, CA: Geothermal Resources Council, October 4, 2017. https://publications.mygeoenergynow.org/grc/1033909.pdf.

EIA. “Annual Energy Outlook 2015 with Projections to 2040.” Annual Energy Outlook. Washington, D.C.: U.S. Energy Information Administration, 2015. https://www.eia.gov/outlooks/archive/aeo15/.

Oladosu, Gbadebo, Lindsay George, and Jeremy Wells. “2020 Cost Analysis of Hydropower Options at Non-Powered Dams.” Oak Ridge, TN: Oak Ridge National Laboratory, 2021. https://doi.org/10.2172/1770649.

DOE. “Hydropower Vision: A New Chapter for America’s Renewable Electricity Source.” Washington, D.C.: U.S. Department of Energy, 2016. https://doi.org/10.2172/1502612.

O’Connor, Patrick W., Scott T. DeNeale, Dol Raj Chalise, Emma Centurion, and Abigail Maloof. “Hydropower Baseline Cost Modeling, Version 2.” Oak Ridge, TN: Oak Ridge National Laboratory, 2015. https://doi.org/10.2172/1244193.

Schmitt, Tommy, Sarah Leptinsky, Marc Turner, Alex Zoelle, Chuck White, Sydney Hughes, Sally Homsy, et al. “Cost And Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity.” Pittsburgh, PA: National Energy Technology Laboratory, October 14, 2022. https://doi.org/10.2172/1893822.

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