Commercial PV
Units using capacity above represent kWDC.
2025 Annual Technology Baseline (ATB) data for commercial solar photovoltaics (PV) are shown above, with a base year of 2023. The Base Year estimates rely on modeled capital expenditures (CAPEX) and operations and maintenance (O&M) cost estimates benchmarked with industry and historical data. The 2025 ATB presents capacity factor estimates that encompass a range associated with advanced, moderate, and conservative technology innovation scenarios across the United States. The 2025 commercial-scale solar PV ATB, for the first time, has analyses for a Research and Development (R&D) cost drivers case and a broader Expanded cost drivers case, with each having assumptions for the set of underlying drivers that affects costs:
- R&D cost drivers case: Estimates costs based on R&D-driven improvements only, as applied to technologies and conditions existing during the most recent year with historical data.
- Expanded cost drivers case: Estimates costs based on R&D-driven improvements plus other cost drivers, such as changing market and supply chain conditions.
These definitions are explained further in the Financial Cases & Methods page. Future year projections for each cost drivers case are derived from bottom-up benchmarking of PV CAPEX and bottom-up engineering analysis of O&M costs. The year 2024 reflects the most recent historical data, derived from benchmarks made in the first quarter of 2024. Specific projections are made for 2030, 2040, 2050, and 2060. Straight lines interpolate between the 2024 and 2030 values, between the 2030 and 2040 values, between the 2040 and 2050 values, and between the 2050 and 2060 values. Cost fluctuations that may occur between each set of years are not represented, such as the fluctuations because of policy and market conditions that occurred after the first quarter of 2024.
Each cost drivers case has three projection scenarios for technology advancement and evolution as follows:
- Conservative Scenario: lower levels of R&D investment with minimal technology advancement and market conditions that result in domestically produced PV components
- Moderate Scenario: R&D investment continuing at similar levels as today, with corresponding levels of technological advancement, and market conditions allowing for component price reductions consistent with trends from the past several years
- Advanced Scenario: an increase in R&D spending generates substantial innovation that drives down costs; market conditions reflect improved access to global markets.
Detailed descriptions of the scenarios are presented in the Scenario Descriptions section of this page. Costs within any given year and for any given project can vary based on site-specific or larger market factors. The chart below shows the 2025 ATB R&D and Expanded cases' CAPEX trajectories for commercial PV in the context of historical ranges.
Historical Sources: (DOE, 2024); (Barbose et al., 2024); (Ramasamy et al., 2022); (Ramasamy et al., 2023).
Future Projections: 2025 ATB.
All prices quoted in WAC are converted to WDC (1 WAC = ILR × WDC).
Resource Categorization
The 2025 ATB provides the average capacity factor for 10 resource categories in the United States, binned by mean global horizontal irradiance (GHI). Average capacity factors are calculated using county-level capacity factor averages from the Renewable Energy Potential (reV) model for 2012 from the National Solar Radiation Database (NSRDB). The NSRDB provides modeled spatiotemporal solar irradiance resource data at 4-kilometer (km) spatial resolution and 0.5-hour temporal resolution. The county-level mean GHI is calculated by aggregating each NSRDB point’s multiyear mean GHI to provide a county’s mean GHI for all years included in the analysis. The U.S. average capacity factor for each resource category is weighted by the land area (square miles) of each county within the GHI resource category. The county estimated land area is provided by geospatial and tabular data from the U.S. Census. The map below shows average annual GHI in the United States.
The following table summarizes the estimated 2019 capacity factors (in the first year of operation) for each resource category and each resource category's associated population.
| Resource Class | GHI Bin (kilowatt-hours/square meters/day [kWh/m2/day]) | Mean Direct Current (DC) Capacity Factor | Population |
|---|---|---|---|
| 1 | >5.75 | 19.8% | 12,554,678 |
| 2 | 5.5–5.75 | 19.1% | 21,403,290 |
| 3 | 5.25–5.5 | 18.0% | 13,476,871 |
| 4 | 5–5.25 | 17.1% | 30,603,630 |
| 5 | 4.75–5 | 16.3% | 45,176,116 |
| 6 | 4.5–4.75 | 16.1% | 39,880,837 |
| 7 | 4.25–4.5 | 15.3% | 31,742,606 |
| 8 | 4–4.25 | 14.6% | 80,155,804 |
| 9 | 3.75–4 | 14.0% | 40,755,023 |
| 10 | <3.75 | 12.7% | 10,255,830 |
| U.S. Mean | 15.8% |
Scenario Descriptions
| Year | Module Efficiency | Inverter Power Electronics | Installation Efficiencies |
|---|---|---|---|
| 2030 | Technology Description: A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: Module efficiency (24%) is based on the International Technology Roadmap for Photovoltaic (ITRPV) projected 2030 Tunnel Oxide Passivated Contact (TOPCon) and Passivated Emitter and Rear Cell (PERC) module efficiency. TOPCon is assumed to almost fully constitute the market, with some PERC presence. This scenario assumes similar proportions of U.S. manufacturing and imported products as existed in 2024, with no product improvements beyond efficiency increases. The 2024 module market price ($0.34/watts direct current [WDC]) and efficiency (21%) from the U.S. Department of Energy (DOE, 2024) are adjusted for 2030 module efficiency, resulting in a module cost of $0.34/WDC. Expanded case: This scenario assumes module price increases because of significant trade barriers and U.S. manufacturers scaling up capacity, with PERC constituting the entire market at an efficiency of 22%. National Laboratory of the Rockies (NLR) internal analysis projected the cost of a potential fully U.S. manufactured modules market, resulting in a module cost of $0.55/WDC. Justification: This scenario represents the low end of projected module efficiency and high end of cost projections. | Technology Description: R&D case: A modeled market price (MMP) is assumed, resulting in an inverter price of $0.06/WDC. Expanded case: A 20% increase in inverter costs is assumed because of trade barriers. An MMP basis results in an inverter price of $0.07/WDC. Justification: Increasing trade barriers and reliance on domestic manufacturing may result in higher costs, reflected in the Expanded case. The R&D case represents a conservative projection of inverter prices. | BOS and labor costs decrease proportionally to the increase in module efficiency.
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| 2040 | Technology Description: A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: Module efficiency (25%) uses ITRPV projected TOPCon module efficiency extrapolated to 2040. TOPCon is assumed to fully constitute the market. This scenario assumes similar proportions of U.S. manufacturing and imported products as existed in 2024, with no product improvements beyond efficiency increases. The 2024 module market price ($0.34/WDC) and efficiency (21%) from (DOE, 2024) are adjusted for 2040 module efficiency, resulting in a module cost of $0.33/WDC. Expanded case: This scenario assumes module price increases because of significant trade barriers and U.S. manufacturers scaling up capacity, with an interpolated module efficiency of 23%. NLR internal analysis projected the cost of a potential fully U.S. manufactured modules market, resulting in a module cost of $0.53/WDC. Justification: This scenario assumes limited improvements in technology efficiency. Market disruptions are not fully resolved in the Expanded case. Module manufacturing is fully scaled up and efficient in the R&D case. | No change vs. 2024.
| BOS and labor costs decrease proportionally to the increase in module efficiency.
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| 2050 | Technology Description: A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: This scenario assumes similar proportions of U.S. manufacturing and imported products as existed in 2024, with no product improvements beyond efficiency increases. Module efficiency (25%) is extrapolated from the 2040 projected efficiency. The 2024 module market price ($0.34/WDC) and efficiency (21%) from (DOE, 2024) are adjusted for 2050 module efficiency, resulting in a module cost of $0.32/WDC. Expanded case: This scenario assumes module price increases because of significant trade barriers and U.S. manufacturers scaling up capacity, with an interpolated module efficiency of 23%. NLR internal analysis projected the cost of a potential fully U.S. manufactured modules market, resulting in a module cost of $0.52/WDC. Justification: This scenario assumes limited improvements in technology efficiency. Market disruptions are not fully resolved in the Expanded case. Module manufacturing is fully scaled up and efficient in the R&D case. | No change vs. 2024.
| BOS and labor costs decrease proportionally to the increase in module efficiency. |
| 2060 | Technology Description: R&D case: This scenario assumes module costs remain the same beyond 2050, at $0.32/WDC. Expanded case: A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. This scenario assumes higher module prices because of significant trade barriers, relatively small U.S. manufacturer capacity, and TOPCon constituting the entire market with an efficiency of 24%. 🗨NREL internal analysis projected the cost of a potential fully U.S. manufactured modules market, resulting in a module cost of $0.50/WDC. Justification: 🗨🗨This scenario assumes limited improvements in technology efficiency. Market disruptions are not fully resolved in the Expanded case. Module manufacturing is fully scaled up and efficient in the R&D case. | No change vs. 2024.
| R&D case: This case assumes BOS and installation labor costs remain the same beyond 2050. Expanded case: BOS and labor costs decrease proportionally to the increase in module efficiency. |
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| References | (DOE, 2024) |
| Year | Module Efficiency | Inverter Power Electronics | Installation Efficiencies |
| 2030 | Technology Description: Efficiency of 24% is calculated using the weighted average of ITRPV projected efficiency and market shares of module technology types, with TOPCon constituting more than half the market.
A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: This scenario assumes a 35% reduction from the 2024 MMP for modules, resulting in $0.25/WDC. Expanded case: 2024 module price is projected to 2030 using 2/3 of the rate of decline observed during 2018–2024 (EIA, 2023), resulting in $0.29/WDC. Justification: 🗨This scenario represents business as usual with a moderate short-term module efficiency-improvement expectation and a module price reduction following historical rates. | No change vs. 2024.
| Technology Description: This scenario assumes 10% labor and hardware BOS cost improvements over the 2024 market price through automation and preassembly efficiencies (e.g., module mounting and wiring) and through higher labor productivity (e.g., through better workforce training) and access to advanced hardware technologies. Justification: This scenario represents lower levels of improvement compared to the long-term historical average (Ramasamy et al., 2025). |
| 2040 | Technology Description: ITRPV market shares and efficiencies are linearly extrapolated to 2040, and efficiency is calculated using a weighted average approach, resulting in 26%.
A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: This scenario assumes a 55% reduction from the 2024 MMP for modules, resulting in $0.18/WDC. Expanded case: Module price decreases from 2030 by 1/2 of the U.S. Energy Information Administration (EIA) 🗨(EIA, 2023) rate from 2018 to 2024, reaching $0.21/WDC. Justification: This scenario represents business as usual with a moderate short-term module efficiency-improvement expectation and a module price reduction following historical rates. | Technology Description: R&D case: This scenario assumes inverter design simplification and manufacturing automation result in an inverter price of $0.05/WDC. Expanded case: This scenario assumes increased access in the market to advanced technologies, resulting in an inverter price of $0.04/WDC. Justification: The power electronics industry already has roadmaps to simplify and automate current products, and there is more potential with increased industry size.
| Technology Description: This scenario assumes 35% labor and hardware BOS cost improvements over the 2024 market price through automation and preassembly efficiencies (e.g., module mounting and wiring) and through higher labor productivity (e.g., through better workforce training) and access to advanced hardware technologies. Justification: This scenario represents lower levels of improvement compared to the long-term historical average (Ramasamy et al., 2025). With increased global deployment and a more efficient supply chain, preassembly of module mounting and wiring is possible. |
| 2050 | Technology Description: Efficiency is calculated as the average of the 2040 and 2060 moderate case projected efficiencies, resulting in 27%. A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: This scenario assumes a 65% reduction from the 2024 MMP for modules, resulting in $0.14/WDC. Expanded case: Module price reduces from 2040 by 1/4 of the EIA rate 🗨(EIA, 2023) from 2018 to 2024, resulting in $0.18/WDC. Justification: This scenario represents business as usual with a moderate short-term module efficiency-improvement expectation and a module price reduction following historical rates. | Technology Description: R&D case: This scenario assumes inverter design simplification and manufacturing automation result in an inverter price of $0.045/WDC. Expanded case: This scenario assumes increased access in the market to advanced technologies, resulting in an inverter price of $0.026/WDC. Justification: The power electronics industry already has roadmaps to simplify and automate current products, and there is more potential with increased industry size. | Technology Description: This scenario assumes 40% labor and hardware BOS cost improvements from 2024 market price through automation and preassembly efficiencies (e.g., module mounting and wiring) and through higher labor productivity (e.g., through better workforce training) and access to advanced hardware technologies. Justification: This scenario represents lower levels of improvement compared to the long-term historical average (Ramasamy et al., 2025). With increased global deployment and a more efficient supply chain, preassembly of module mounting and wiring is possible. Best practices for permitting interconnection and PV installation (e.g., subdivision regulations, new construction guidelines, and design requirements) are being developed. |
| 2060 | Technology Description: A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: This scenario assumes module costs remain the same beyond 2050, at $0.14/WDC. Expanded case: Assumes a lower end of module efficiency at 28%.🗨 Module price decreases from 2050 by 1/6 of the EIA rate (EIA, 2023) from 2018 to 2024, resulting in a module price of $0.17/WDC. Justification: This scenario represents business as usual with a moderate short-term module efficiency-improvement expectation and a module price reduction following historical rates. | Technology Description: R&D case: This scenario assumes inverter costs remain the same beyond 2050, at $0.045/WDC. Expanded case: This scenario assumes increased access in the market to advanced inverter technologies, resulting in an inverter price of $0.01/WDC. Justification: The electronics industry already has roadmaps to simplify and automate current products, and there is more potential with increased industry size and longer timelines. | Technology Description: R&D case: This scenario assumes labor and hardware BOS costs remain the same beyond 2050. Expanded case: This scenario assumes 45% labor and hardware BOS cost improvements from the market price in 2024 through better availability of labor and access to advanced hardware technologies. Justification: This scenario represents lower levels of improvement compared to the long-term historical average (Ramasamy et al., 2025). With increased global deployment and a more efficient supply chain, preassembly of module mounting and wiring is possible. Best practices for permitting, interconnection, and PV installation (e.g., subdivision regulations, new construction guidelines, and design requirements) are being developed. |
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| References |
| Year | Module Efficiency | Inverter Power Electronics | Installation Efficiencies |
| 2030 | Technology Description: This scenario assumes rapid improvements in module efficiency, based on ITRPV projected 2030 module efficiency with removal of PERC and increased tandem PV presence, resulting in a weighted average efficiency of 25%.
A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: The MMP is adjusted for module efficiency improvements, combined with a 45% reduction in costs from manufacturing improvements, resulting in $0.18/WDC. Expanded case: The 2024 global module spot price ($0.10/WDC) and efficiency (21%) from (DOE, 2024) are adjusted for 2030 module efficiency, resulting in a module cost of $0.10/WDC. Justification: This scenario represents a more aggressive technological scenario with rapid shifts to high-efficiency module technologies and, in the Expanded case, assumes access to global market pricing. | Technology Description: R&D case: This scenario assumes inverter design simplification and manufacturing automation result in an inverter price of $0.045/WDC. Expanded case: This scenario assumes inverter design simplification and manufacturing automation result in an inverter price of $0.03/WDC. Justification: The power electronics industry already has roadmaps to simplify and automate current products, and there is more potential with increased industry size. | Technology Description: This scenario assumes a 30% reduction from 2024 prices in BOS equipment and installation labor costs. This is achieved through automation and preassembly efficiencies (e.g., module mounting and wiring) and through better availability of labor and access to advanced hardware technologies. The use of carbon fiber—which is assumed to have achieved low cost, replacing steel and aluminum—cuts mounting costs. R&D case: 2024 market price basis is used. Expanded case: 2024 minimum sustainable price basis is used. Justification: With increased global deployment and a more efficient supply chain, preassembly of PV module mounting and wiring is possible. Reduction of supply chain margins (e.g., profit and overhead charged by suppliers, manufacturers, distributors, and retailers) will likely occur as the U.S. PV industry grows and matures. In addition, streamlining of installation practices through improved workforce development and training and developing standardized PV hardware is assumed.
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| 2040 | Technology Description: This scenario assumes rapid improvements in module technology efficiency. Module efficiency uses ITRPV projected efficiency extrapolated to 2040 and significant market growth of tandem PV technology because of advances in durability and manufacturing techniques. This results in a weighted average module efficiency of 28%.
A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: The MMP is adjusted for module efficiency improvements, combined with a 50% reduction in costs from manufacturing improvements, resulting in $0.15/WDC. Expanded case: The 2024 global module spot price ($0.10/WDC) and efficiency (21%) from (DOE, 2024) are adjusted for 2040 module efficiency, resulting in a module cost of $0.09/WDC. Justification: This scenario represents a more aggressive technological scenario with rapid shifts to high-efficiency module technologies and, in the Expanded case, assumes access to global market pricing. | Technology Description: R&D case: This case assumes inverter costs remain the same beyond 2030, at $0.045/WDC. Expanded case: This scenario assumes inverter design simplification and manufacturing automation result in an inverter price of $0.02/WDC. Justification: The power electronics industry already has roadmaps to simplify and automate current products, and there is more potential with increased industry size.
| Technology Description: This scenario assumes a 40% reduction from 2024 prices in BOS equipment and installation labor costs. This is achieved through automation and preassembly efficiencies (e.g., module mounting and wiring) and through better availability of labor and access to advanced hardware technologies. The use of carbon fiber—which is assumed to have achieved low cost, replacing steel and aluminum—cuts mounting costs. R&D case: 2024 market price basis is used. Expanded case: 2024 minimum sustainable price basis is used. Justification: The types of technology improvements are similar to those for the 2030 scenario above, with similar justification but more aggressive.
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| 2050 | Technology Description: Module efficiency (30%) is the average between 2040 and 2060 projected efficiency values. A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. R&D case: The MMP is adjusted for module efficiency improvements, combined with a 55% reduction in costs from manufacturing improvements, resulting in $0.12/WDC. Expanded case: The 2024 global module spot price ($0.10/WDC) and efficiency (21%) from (DOE, 2024) are adjusted for 2050 module efficiency, resulting in a module cost of $0.08/WDC. Justification: This scenario represents a significant improvement in module efficiency and, in the Expanded case, assumes access to global market pricing. | Technology Description: R&D case: This scenario assumes inverter costs remain the same beyond 2030, at $0.045/WDC. Expanded case: This scenario assumes inverter design simplification and manufacturing automation result in an inverter price of $0.02/WDC. Justification: The power electronics industry already has roadmaps to simplify and automate current products, and there is more potential with increased industry size.
| Technology Description: This scenario assumes a 50% reduction from 2024 prices in BOS equipment and installation labor costs. This is achieved through automation and preassembly efficiencies (e.g., module mounting and wiring) and through better availability of labor and access to advanced hardware technologies. The use of carbon fiber—which is assumed to have achieved low cost, replacing steel and aluminum—cuts mounting costs. R&D case: 2024 market price basis is used. Expanded case: 2024 minimum sustainable price basis is used. Justification: The types of technology improvements are similar to those for the 2040 scenario above, with similar justification but more aggressive. |
| 2060 | Technology Description: R&D case: This case assumes module costs remain the same beyond 2050, at $0.12/WDC. Expanded case: This scenario assumes rapid improvements in module technology efficiency as well as new technologies entering the market. NLR internal analysis projected the potential technology market share and module efficiency of a 2060 market (Kirstin Alberi et al., 2024); (Thomas G. Allen et al., 2024), resulting in a weighted average module efficiency of 32%.
A 17% supply chain premium based on the difference between utility module prices and rooftop module prices in (DOE, 2024) is applied to rooftop module costs. The 2024 global module spot price ($0.10/WDC) and efficiency (21%) from (DOE, 2024) are adjusted for 2060 module efficiency, resulting in a module cost of $0.08/WDC. Justification: This scenario represents a significant improvement in module efficiency and, in the Expanded case, assumes access to global market pricing. | Technology Description: R&D case: This case assumes inverter costs remain the same beyond 2030, at $0.045/WDC. Expanded case: This scenario assumes inverter design simplification and manufacturing automation result in an inverter price of $0.01/WDC. Justification: The power electronics industry already has roadmaps to simplify and automate current products, and there is more potential with increased industry size.
| Technology Description: R&D case: This scenario assumes BOS and installation labor costs remain the same beyond 2050. Expanded case: This scenario assumes a 55% reduction from 2024 minimum sustainable prices in BOS equipment and installation labor costs through better availability of labor and access to advanced hardware technologies. A significant step change in the use of emerging technologies impacts the reduction of system costs. Justification: Innovative technologies enter the market, increasing system efficiency and decreasing costs.
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| References | (DOE, 2024) |
Scenario Assumptions
The technology improvement scenarios are used to project CAPEX for utility-scale PV with linear interpolation between each target year, which results in CAPEX changes as described in the tables below.
R&D Case CAPEX Changes
| Year | Conservative Scenario | Moderate Scenario | Advanced Scenario | |||
| Total | Per Year | Total | Per Year | Total | Per Year | |
| 2024–2030 | -6% | -1.1% | -21% | -3.8% | -39% | -8.0% |
| 2030–2040 | -2% | -0.2% | -28% | -3.3% | -20% | -2.2% |
| 2040–2050 | -2% | -0.2% | -15% | -1.7% | -17% | -1.8% |
| 2050–2060 | 0% | 0% | 0% | 0% | 0% | 0% |
Expanded Case CAPEX Changes
| Year | Conservative Scenario | Moderate Scenario | Advanced Scenario | |||
| Total | Per Year | Total | Per Year | Total | Per Year | |
| 2024 –2030 | 19% | 2.9% | -18% | -3.2% | -51% | -11.3% |
| 2030–2040 | -4% | -0.4% | -27% | -3.1% | -20% | -2.2% |
| 2040–2050 | -2% | -0.2% | -15% | -1.6% | -17% | -1.8% |
| 2050–2060 | -2% | -0.2% | -12% | -1.3% | -13% | -1.3% |
Although we did not create our CAPEX projections based on rates of deployment, commercial PV deployment is expected to increase substantially over our analysis period. For example, in the National Laboratory of the Rockies's (NLR's) Standard Scenarios Mid-case, U.S. distributed PV deployment (including commercial and other distributed systems such as residential systems) grows by 222% between 2024 and 2035 (from 41 gigawatts [GW] to 131 GW) and by 32% between 2035 and 2050 (from 131 GW to 173 GW) (Gagnon et al., 2024) .
Representative Technology
For the 2025 ATB, commercial PV systems are modeled for a 200-kilowatt direct current (kWDC), flat-roof-mounted system with a 1.23 DC-to-AC (alternating current) ratio, or inverter loading ratio (ILR) (Ramasamy et al., 2022). Flat-plate PV can use direct or indirect insolation, so PV modules need not directly face and track incident radiation. The county-level capacity factors are calculated for specific locations, which are based on representative agents selected in the Distributed Generation Market Demand Model (dGen) 2020 Standard Scenarios agent database (Sigrin et al., 2016). At each location, various tilt/azimuth combinations are evaluated and the optimal combination is chosen for modeling. The ability to use direct and indirect insolation gives rooftop PV systems a broad geographical application. A study of rooftop PV technical potential (Gagnon et al., 2016) estimated as much as 731 GW (926 terawatt-hours per year [TWh/yr]) of potential exists for small buildings (<5,000-square-meter [m2] footprint) and 386 GW (506 TWh/yr) exists for medium (5,000–25,000 m2) and large (>25,000 m2) buildings.
Methodology
This section describes the methodology to develop assumptions for CAPEX, O&M, and capacity factor. For standardized assumptions, see regional cost variation, materials cost index, scale of industry, policies and regulations, and inflation. The PV-specific and standardized assumptions for labor costs differ; the PV analysis assumes the use of nonunion labor only.
Currently, CAPEX—not levelized cost of energy (LCOE)—is the most common metric for PV costs. Because of different assumptions in long-term incentives, system location and production characteristics, and cost of capital, LCOE can be confusing and often noncomparable for different estimates. Although CAPEX also has many assumptions and interpretations, managing it involves fewer variables. Therefore, PV projections in the 2025 ATB are driven entirely by plant and operating cost improvements.
The Base Year estimates rely on modeled CAPEX and O&M estimates benchmarked with industry and historical data. Capacity factor is estimated based on hours of sunlight at latitude for 10 resource categories in the United States, binned by mean GHI.
Future year projections are derived from bottom-up benchmarking of PV CAPEX and bottom-up engineering analysis of O&M costs. Three projections are developed for scenario modeling as bounding levels (see the scenario list above).
Capital Expenditures (CAPEX)
Definition: Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. For commercial PV, CAPEX is modeled only for a host-owned business model with access to debt.
For the 2025 ATB—and based on the NLR PV cost model (Ramasamy et al., 2022)—the distributed PV plant envelope is defined to include items noted in the Components of CAPEX table below.
Base Year: In the historical trends chart above, reported historical commercial-scale PV installation CAPEX (Barbose et al., 2024) is shown in box-and-whiskers format through 2023 along with benchmarked CAPEX in 2022 (Ramasamy et al., 2022) and 2024 and projections from the 2025 ATB; the 2024 benchmark is based on (Ramasamy et al., 2022), with market adjustments from (DOE, 2024).
Reported and benchmarked prices can differ for various reasons, as outlined by Barbose and Darghouth (Barbose et al., 2019); Bolinger, Seel, and Robson (Bolinger et al., 2019); and (Ramasamy et al., 2022), including the following:
- Timing-Related Issues: For example, the time between contract completion and project placement in service may vary.
- System Variations: The size, technology, installer margin, and design of systems installed in a given year vary over time.
- Cost Categories: There are variations in which cost categories are included in CAPEX (e.g., financing costs and initial O&M expenses).
Federal investment tax credits provide an incentive to include costs in the upfront CAPEX to receive a higher tax credit; these included costs may have otherwise been reported as operating costs. The bottom-up benchmarks are more reflective of overnight capital costs, which is consistent with the ATB methodology of inputting overnight capital costs and calculating construction financing to derive CAPEX.
Commercial PV pricing and capacities are quoted in kWDC (i.e., module rated capacity) unlike other generation technologies (including utility-scale PV), which are quoted in kWAC. This is because kWDC is the unit used by most of the PV industry. Although costs are reported in kWDC, the total CAPEX includes the cost of the inverter, which has a capacity measured in kWAC.
CAPEX estimates for 2024 reflect the analysis of system costs and pricing for projects that became operational in 2022 (Ramasamy et al., 2022); (DOE, 2024).
The chart above shows the range in historical CAPEX that reflects the heterogeneous composition of the commercial PV market in the United States. The chart includes a representative commercial-scale PV installation. Although commercial PV systems vary dramatically in size and application, typical installation costs are represented with a single estimate per innovation scenario. In addition, commercial PV CAPEX does not correlate well with solar resources.
Although the technology market share may shift over time with new developments, the typical installation costs are represented with the projections above.
System prices of $1.85/WDC in 2023 and $1.66/WDC in 2024 are based on bottom-up benchmark analysis reported by (Ramasamy et al., 2022), with market adjustments for 2024 from (DOE, 2024). The 2023 and 2024 bottom-up benchmarks are reflective of overnight capital costs, which are consistent with the ATB methodology of inputting overnight capital costs and calculating construction financing to derive CAPEX.
The Base Year CAPEX estimates should tend toward the low end of observed costs because no regional impacts are included. These effects are represented in the historical market data.
Future Years: Projections of commercial PV plant CAPEX for future years 2030, 2040, 2050, and 2060 are based on bottom-up cost modeling, with 2022 values from (Ramasamy et al., 2022)—adjusted for the 2024 market based on (DOE, 2024) and a straight-line change in price in the intermediate years between each pivot year. The assumptions for the R&D cost drivers and Expanded cost drivers cases vary, which results in different sets of results from the bottom-up cost model. The system design and price changes made in the models are summarized and described in the Summary of Technology Innovations by Scenario table. See below for the details of changes to components of system price in the various ATB scenarios.
The values in the chart above represent overnight capital costs, which exclude construction financing costs.
We assume a straight-line change in price in the years between 2024 and 2030, between 2030 and 2040, between 2040 and 2050, and between 2050 and 2060.
We compare the R&D cost case CAPEX scenarios over time to three analyst projections—one from the U.S. Energy Information Administration (EIA) and two from private analysts—adjusted for inflation. The median of the private projections is displayed in the figure below through 2030, along with the EIA projection through 2050. The 2025 ATB Advanced Scenario CAPEX projection generally aligns with the median analyst projection through 2030, whereas all ATB projections are lower than the EIA projection through 2050.
Sources: 2025 ATB; (DOE, 2024); (Wood Mackenzie, 2024); (EIA, 2023); (BNEF, 2024); (Ramasamy et al., 2023).
All prices quoted in WAC are converted to WDC (1 WAC = ILR × WDC).
Use the following table to view the components of CAPEX.
Operation and Maintenance (O&M) Costs
Definition: O&M costs represent the annual expenditures required to operate and maintain a PV plant over its lifetime, including items noted in the table below.
Base Year: The initial figure on this page shows the Base Year estimate and future year projections for fixed O&M (FOM) costs. Three technology innovation scenarios are represented. The estimate for a given year represents annual average FOM costs expected over the technical lifetime of a new plant that reaches commercial operation in that year.
The FOM cost of $20/kWDC-yr is based on modeled pricing for a commercial PV system quoted in 2023 as reported by (Ramasamy et al., 2022). Lawrence Berkeley National Laboratory collected feedback from U.S. solar industry professionals (Wiser et al., 2020). The wide range in reported prices is in part because of the maintenance practices that exist for a particular system. These cost categories include asset management (including compliance and reporting for incentive payments), insurance products, site security, cleaning, vegetation removal, and component failure. Not all these practices are performed for each system; in addition, some factors depend on the quality of the parts and construction.
Future Years: The FOM cost of approximately $17.63/kWDC-yr for 2024 is based on pricing reported by (Ramasamy et al., 2022) and (DOE, 2024), which can be divided into system-related expenses ($14.17/kWDC-yr) and administration-related expenses ($3.46/kWDC-yr). From 2024 to 2060, system-related FOM is based on the ratio of O&M costs ($/kW-yr) to CAPEX costs ($/kW), which was 0.85:100 in 2024 based on (Ramasamy et al., 2022) and (DOE, 2024). Historical data suggest O&M and CAPEX cost reductions are correlated; from 2010 to 2020, benchmark commercial PV O&M and CAPEX costs fell 53% and 77%, respectively, as reported by (Ramasamy et al., 2025). Administrative expenses are kept constant.
Use the following table to view the components of O&M.
Capacity Factor
Definition: The capacity factor for commercial PV systems is not directly comparable to other technologies' capacity factors. Other technologies' capacity factors (including utility-scale PV) are represented exclusively in AC units (see Solar PV AC-DC Translation). However, because commercial PV pricing in the 2025 ATB is represented in $/WDC, commercial PV system capacity is a DC rating. Because each technology uses consistent capacity ratings, the LCOEs are comparable.
The capacity factor is influenced by the hourly solar profile, technology (e.g., thin-film or crystalline silicon), bifaciality of the module, shading, expected downtime, and inverter losses to transform from DC power to AC power. The DC-to-AC ratio is a design choice that influences the capacity factor. The baseline PV plant capacity factor incorporates an assumed degradation rate of 0.7%/yr in the annual average calculation. R&D could increase energy yield through bifaciality, increased albedo, better soil removal, improved cell temperature, lower system losses, O&M practices that improve uptime, and lower degradation rates of PV plant capacity factor.
Base Year: In the interactive data chart at the top of this page, select Technology Detail = All to add filters showing a range of capacity factors based on variation in solar resource across the contiguous United States. The range of the Base Year estimates illustrates the effect of locating a commercial PV plant in places with lower or higher solar irradiance. The ATB provides the average capacity factor for 10 resource categories in the United States, binned by mean GHI. The annual average capacity factor for the contiguous United States is calculated using the reV model using solar resource data from the NSRDB. The county-level capacity factors are calculated for specific locations with azimuth and tilt, which are based on representative agents selected in the Distributed Generation Market Demand Model (dGen) 2020 Standard Scenarios agent database (Sigrin et al., 2016). A lookup table for these locations and the NSRDB is generated based on nearest distance. The azimuth and tilt as well as the resource GHI are used to generate a System Advisor Model (SAM) configuration file and run reV, which outputs the annual average capacity factor at each evaluated location. The U.S. average capacity factor for each resource category is weighted by the population of each county within the GHI resource category. The county estimated populations are provided by geospatial and tabular data from the U.S. Census.
Because of the change in methodology in calculating capacity factors in the 2025 ATB, capacity factors are not directly comparable to some previous editions of the ATB. First-year (2019) operation capacity factors as modeled range from 12.7% for Class 10 (for locations with an average annual GHI less than 3.75) to 19.8% for Class 1 (for locations with an average annual GHI greater than 5.75).
Over time, PV installation output is reduced because of degradation in module quality, which is accounted for in ATB estimates of capacity factor over the 30-year lifetime of the plant. The adjusted average capacity factor values in the 2025 ATB Base Year range from 11.7% for Class 10 (for locations with an average annual GHI less than 3.75) to 19.4% for Class 1 (for locations with an average annual GHI greater than 5.75).
Future Years: Projections of capacity factors for plants installed in future years increase over time because of an increase in energy yield from the module (improved cell temperature and bifaciality), reduced system losses (improved soil removal, improved O&M uptime, and more efficient inverters), and a reduction in degradation rates. The table below summarizes the technology improvements we use to calculate indicative improvements in capacity factor in each scenario.
| Performance Area | 2019* | 2035 Conservative Scenario | 2035 Moderate Scenario | 2035 Advanced Scenario |
| Bifaciality | None | None | 0.85 | 0.85 |
| AC and DC losses | 14.3% | 14.3% | 10.4% | 7.5% |
| Annual degradation rate | 0.7% | 0.7% | 0.5% | 0.2% |
* The year 2019 is used here because improvement assumptions are not changed from the 2021 ATB with a base year of 2019.
The technology improvements summarized above would not necessarily result in the estimated capacity factor improvements, given the 2025 ATB assumption of a constant ILR. PV system ILR choice is based on an optimization exercise to maximize profits (or offer the lowest energy price), trading off the extra cost and increased clipping losses of additional modules with improvements in inverter operation and a higher, flatter electricity production curve. All things being equal, the optimal ILR of PV systems in higher resource classes or those that use bifacial modules will be lower than the optimal ILR of systems in lower resource classes or those with monofacial modules, particularly without the use of energy storage. Because of the complexity of optimizing CAPEX and ILR for each resource class for each year, and with and without storage, ATB PV system CAPEX and capacity factor benchmarks are calculated using a fixed ILR—independent of system location, performance improvements over time or the incorporation of storage. In addition, we assume performance improvements over time are not location-dependent, even though a PV system with the same ILR in a higher-resource area will experience more clipping and thus fewer performance improvements. However, in reality, PV systems in those areas would reduce their clipping losses by installing fewer PV panels and would thus have a lower upfront cost (trading off the marginally greater production with reduced CAPEX).
The following table summarizes the difference in average capacity factor in 2035 caused by these changes in the technology innovation scenarios. We assume each scenario's 2050 capacity factor is the equivalent of the 2035 capacity factor of the scenario but one degree more aggressive in improvement, with a straight-line change in price in the intermediate years between 2035 and 2050. Capacity factors remain constant between 2050 and 2060. The table below summarizes capacity factors for each ATB scenario by resource class.
| Scenario | Average Capacity Factor in 2035 (Class 10–Class 1) | Percentage Improvement From Base Year (2023) |
|---|---|---|
| Advanced Scenario | 14.9%–23.2% | 19.11% |
| Moderate Scenario | 13.2%–20.5% | 9.15% |
| Conservative Scenario | 11.7%–18.2% | 0% |
We also develop and model a scenario one degree more aggressive than the Advanced Scenario to estimate its 2050 capacity factor. In the Advanced Scenario, the capacity factor has an improvement of 24.1% between 2023 and 2050.
References
The following references are specific to this page; for all references in this ATB, see References.