2020 vs. 2019 Changes

The ATB provides a transparent set of technology cost and performance data for electric sector analysis. The update of the 2019 version of ATB to this 2020 version includes general updates to all technologies and technology-specific updates. Use the following charts to explore the changes between 2019 and 2020.

Parameter value projections by ATB projection year
Compare between 2019 and 2020 ATB. Click "more details" above the chart to select the parameter (LCOE, CAPEX, Fixed O&M, Capacity Factor, and FCR) and other filters.

General Updates to All Technologies

  • The assumptions in each of the two financial assumptions cases were modified to reflect current assessments.
  • The Base Year was updated from 2017 to 2018 using new market data or analysis where applicable.
  • The dollar year was updated from 2017 to 2018 with a 2.4% inflation rate (BLS, 2020).
  • Historical data were updated to include data reported through year end 2018.

Renewable Generation Updates Summary

  • Land-Based Wind: Projections based on bottom-up technology analysis and cost modeling plus learning rates, with innovations that increase wind turbine size, improve controls, and enhance through science-based modeling.
  • Offshore Wind: Projections based on bottom-up techno-economic models and assessment of turbine and plant upsizing innovations, supply chain efficiencies and learning, and innovations identified through expert reviews.
  • Utility-scale Photovoltaics: Projections based on bottom-up techno-economic analysis of effects of improved module efficiency, inverters, installation efficiencies from assembly and design, all attributable to technological innovation.
  • Concentrating Solar Power: Component and system cost estimates for Base Year now reference a 2017 industry survey, and a 2018 cost analysis of recent market developments.
  • Geothermal: New data are now consistent with GeoVision Study.
  • Lithium-ion Battery Storage: Updated projections are based on a new literature review.

Technology-Specific Updates

Land-Based Wind

  • Base Year: Capital expenditures (CAPEX) associated with wind plants installed in the interior of the country are used to characterize CAPEX for hypothetical wind plants with average annual wind speeds that correspond with the median conditions for recently installed wind facilities based on the 2018 Cost of Wind Energy Review (Stehly et al., 2019). The O&M of $44/kW-yr is also estimated (Stehly et al., 2019); no variation of FOM with wind speed class is assumed. Capacity factors align with performance in wind speed classes 2–7, where most installations are located.
  • Projections: Specific technology innovations are associated with each scenario. In the Moderate Technology Innovation Scenario (Moderate Scenario), large segmented blades are transported by truck, enabling larger rotors. Segmentation enables higher hubs and larger turbines, and advanced controls enable higher capacity factors. In the Advanced Technology Innovation Scenario (Advanced Scenario), even larger turbines and advanced rotor configurations increase turbine capacity, on-site manufacturing further increases hubs, and high-fidelity modeling and advanced controls are fully implemented.

Offshore Wind

  • Base Year: CAPEX was derived from bottom-up modeling using an updated version of NREL's Offshore Regional Cost Analyzer (ORCA) (Beiter et al., 2016), considering various spatial parameters, and calibrated the latest cost and technology trends observed in the U.S. and European offshore wind markets (Beiter et al., 2019), (Walter Musial et al., 2019). Capacity factors were determined using a representative power curve for a generic NREL-modeled 6-MW offshore wind turbine (Beiter et al., 2016) and includes geospatial estimates of gross capacity factors for the entire resource (Walt Musial et al., 2016).
  • Projections: Specific technology innovations are associated with each scenario. In the Moderate Scenario, 15-MW turbines are used, requiring retooling and component changes. In the Advanced Scenario, 18-MW turbines are used, requiring advances in materials and transportation. Supply chain efficiency increase more rapidly, and wind farm optimization, high-fidelity modeling, and advanced controls are fully implemented.

Photovoltaics (Utility-scale, Commercial, Residential)

  • Base Year: CAPEX for 2018 and 2019 are based on new bottom-up modeling and market data from Feldman et al. (2020), which focused on larger systems to align with market trends. The O&M costs are based on modeled pricing for a 100-MWDC, one-axis tracking systems (Feldman et al., Forthcoming). The O&M values in the 2020 ATB are higher in than the 2019 ATB because of the change from $/WDC to using $/WAC. The 2018 the cumulative capacity-weighted average AC capacity factor for all U.S. projects installed is 25.0% (including fixed-tilt systems).
  • Projections: Projections that were based on literature surveys are now based on bottom-up CAPEX benchmarks. The Moderate Scenario is based on module efficiency gains consistent with PERC n-type mono modules, improved inverter systems, and installation efficiencies due to automation, pre-assembly, and improved design. The Advanced Scenario assumes additional innovations, such as continuation of the historical rate of module efficiency improvement, simplification of inverter design and automation of inverter manufacturing, and greater installation efficiency (Beiter et al., 2016) from pre-assembly, automation, and materials innovations. Estimates for energy yield gain for utility-scale and commercial PV systems are also included.

Concentrating Solar Power (CSP)

  • Base Year: Estimates are based on bottom-up cost modeling from (Turchi et al., 2019) and an NREL survey of projects under construction for operation in 2018.
  • Projections: 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 due to deployment in the solar field. The Advanced Scenario assumes higher temperature supercritical CO2 , higher temperature receiver, advanced storage compatible with higher temperatures, and low-cost, modular solar fields with increased efficiency.

Geothermal

  • Base Year: As before, estimates are based on bottom-up cost modeling using GETEM and inputs from the GeoVision BAU scenario (DOE, 2019).The Base Year was updated to 2018$ dollar year based on the consumer price index and producer price indices.
  • Projections: The projection of future geothermal plant CAPEX for the Advanced Scenario is based on the Technology Improvement scenario from the GeoVision Study ((DOE, 2019) and (Augustine et al., 2019)). The Moderate Scenario is based on the Intermediate 1 Drilling Curve detailed as part of the GeoVision report to 2030, and a minimum learning rate to 2050 as implemented in AEO2015 (EIA, 2015): 10% CAPEX reduction by 2035. The Conservative Technology Innovation Scenario (Conservative Scenario) retains all cost and performance assumptions equivalent to the Base Year through 2050.

Hydropower

  • Base Year: The Base Year was updated to 2018$ dollar year based on the consumer price index.
  • Projections: The ATB hydropower analysis is 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). The projections use a mix of EIA technological learning assumptions, input from a technical team of Oak Ridge National Laboratory researchers, and the experience of expert hydropower consultants.

Lithium-Ion Battery Storage

  • A simple representation of the CAPEX scenarios used in Regional Energy Deployment System (ReEDS) modeling for lithium-ion battery storage is included.

Natural Gas, Coal, Nuclear, and Biopower

  • Cost and performance estimates were updated to match AEO2020 (EIA, 2020).
  • Natural gas and coal fuel costs were updated to match AEO2020 (EIA, 2020).
  • Information about current costs in published literature was updated.

References

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

Augustine, Chad, Ho, Jonathan, & Blair, Nate. (2019). GeoVision Analysis Supporting Task Force Report: Electric Sector Potential to Penetration. (No. NREL/ TP-6A20-71833). National Renewable Energy Laboratory. https://doi.org/10.2172/1524768

Beiter, Philipp, Musial, Walter, Smith, Aaron, Kilcher, Levi, Damiani, Rick, Maness, Michael, Sirnivas, Senu, Stehly, Tyler, Gevorgian, Vahan, Mooney, Meghan, & Scott, George. (2016). A Spatial-Economic Cost-Reduction Pathway Analysis for U.S. Offshore Wind Energy Development from 2015-2030. (No. NREL/TP-6A20-66579). National Renewable Energy Laboratory. https://doi.org/10.2172/1324526

Beiter, Philipp, Spitsen, Paul, Musial, Walter, & Lantz, Eric. (2019). The Vineyard Wind Power Purchase Agreement: Insights for Estimating Costs of U.S. Offshore Wind Projects. (No. NREL/TP-5000-72981). National Renewable Energy Laboratory. https://doi.org/10.2172/1495385

BLS (2020). CPI for All Urban Consumers (CPI-U). U.S. Bureau of Labor Statistics. https://beta.bls.gov/dataViewer/view/timeseries/CUSR0000SA0

DOE (2016). Hydropower Vision: A New Chapter for America's Renewable Electricity Source. (No. DOE/GO-102016-4869). U.S. Department of Energy. https://www.energy.gov/sites/prod/files/2018/02/f49/Hydropower-Vision-021518.pdf

DOE (2019). GeoVision: Harnessing the Heat Beneath Our Feet. (No. DOE/EE–1306). U.S. Department of Energy. https://www.energy.gov/sites/prod/files/2019/06/f63/GeoVision-full-report-opt.pdf

EIA (2015). Annual Energy Outlook 2015 with Projections to 2040. (No. AEO2015). U.S. Energy Information Administration. https://www.eia.gov/outlooks/archive/aeo15/

EIA (2020). Annual Energy Outlook 2020 with Projections to 2050. (No. AEO2020). U.S. Energy Information Administration. https://www.eia.gov/outlooks/aeo/pdf/AEO2020.pdf

Feldman, David, Vignesh Ramasamy, Ran Fu, Ashwin Ramdas, Jal Desai, and Robert Margolis. (Forthcoming). U.S. Solar Photovoltaic System and Energy Storage Cost Benchmark: Q1 2020. Golden, CO: National Renewable Energy Laboratory.

Musial, Walt, Heimiller, Donna, Beiter, Philipp, Scott, George, & Draxl, Caroline. (2016). 2016 Offshore Wind Energy Resource Assessment for the United States. (No. NREL/TP-5000-66599). National Renewable Energy Laboratory. https://www.nrel.gov/docs/fy16osti/66599.pdf

Musial, Walter, Beiter, Philipp, Spitsen, Paul, & Nunemaker, Jake. (2019). 2018 Offshore Wind Technologies Market Report. National Renewable Energy Laboratory. https://www.nrel.gov/docs/fy20osti/74598.pdf

O'Connor, Patrick W., DeNeale, Scott T., Chalise, Dol Raj, Centurion, Emma, & Maloof, Abigail. (2015). Hydropower Baseline Cost Modeling, Version 2. (No. ORNL/TM-2015/471). Oak Ridge National Laboratory. https://info.ornl.gov/sites/publications/files/Pub58666.pdf

Stehly, Tyler, Beiter, Philipp, Heimiller, Donna, & Scott, George. (2019). 2018 Cost of Wind Energy Review. (No. NREL/TP-5000-74598). National Renewable Energy Laboratory. https://www.nrel.gov/docs/fy20osti/74598.pdf

Turchi, Craig, Boyd, Matthew, Kesseli, Devon, Kurup, Parthiv, Mehos, Mark, Neises, Ty, Sharan, Prashant, Wagner, Michael, & Wendelin, Timothy. (2019). CSP Systems Analysis: Final Project Report. (No. NREL/TP-5500-72856). National Renewable Energy Laboratory. https://www.nrel.gov/docs/fy19osti/72856.pdf