Commercial PV
ATB data for commercial solar photovoltaics (PV) are shown above. 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 five representative locations in the United States. The 2020 ATB presents capacity factor estimates that encompass a range associated with advanced, moderate, and conservative technology innovation scenarios across the United States. Future year projections are derived from bottom-up benchmarking of PV CAPEX and bottom-up engineering analysis of O&M costs.
The three scenarios for technology innovation are:
- Conservative Technology Innovation Scenario (Conservative Scenario): lower levels of R&D investment with minimal technology advancement and current global module pricing
- Moderate Technology Innovation Scenario (Moderate Scenario): R&D investment continuing at similar levels as today, with no substantial innovations or new technologies introduced to the market
- Advanced Technology Innovation Scenario (Advanced Scenario): an increase in R&D spending that generates substantial innovation, allowing historical rates of development to continue.
Resource Categorization
Solar resources in the 2020 ATB are categorized according to the range of solar irradiance across the range of latitudes for five resource locations in the contiguous United States:
- Low: Seattle, Washington
- Low-mid: Chicago, Illinois
- Mid: Kansas City, Missouri
- High-mid: Los Angeles, California
- High: Daggett, California.
First-year operation capacity factors as modeled range from 12.4% to 19.5%, though these depend significantly on location and system configuration (e.g., fixed-tilt or single-axis tracking).
Scenario Descriptions
|
Scenario |
Module Efficiency1 |
Inverter and Power Electronics |
Installation Efficiencies |
Energy Yield Gain1 |
|
Conservative |
Technology Description: Tariffs expire, as scheduled, though some form of friction still remains, keeping U.S. panel pricing halfway between current U.S. and global pricing. Efficiency gains for panels are consistent with one standard deviation below International Technology Roadmap for Photovoltaic (ITRPV—an annual document prepared by 55 leading international poly-Si producers, wafer suppliers, c-Si solar cell manufacturers, module manufacturers, PV equipment suppliers, and production material providers, as well as PV research institutes and consultants) to 2030for PERC n-type mono module; well below historical mono average gains and below leveling off point (21.5%) -$0.30/WDC
Justification:Represents the low end of manufacture expectations and additional friction despite the scheduled removal of the tariffs. |
Technology Description: Larger market size
Justification: global PV industry expected to continue to expand |
n/a |
n/a |
|
Moderate |
Technology Description: Tariffs expire, as scheduled, and efficiency gains consistent with median ITRPV roadmap to 2030for PERC n-type mono module; well below historical mono average gains and below leveling off point (22.5%) -$0.19/W
Justification:Represents manufacture expectations for 2030. |
Technology Description: Design simplification and manufacturing automation
Justification: industry currently switching to this practice. |
Technology Description: 30% labor cost improvements through automation, pre-assembly efficiencies, and improvements in wind load design
Justification: represents lower levels of improvement than historical average (Feldman et al. Forthcoming). With increased global deployment and more efficient supply chain, pre-assembly is possible. Development of best practices for permitting interconnection and PV installation, such as subdivision regulations, new construction guidelines, and design requirements. |
Technology Description: 6% energy gain (5% energy yield gain at module), lower system losses, and degradation rate reduction from 0.7%/yr to 0.5%/yr
Justification: Significant R&D is currently spent on improved cell temperatures, and lower degradation rates. Companies will likely continue to focus on improved uptime to maximize profitability, and bifacial modules are already becoming a significant part of the global and U.S. supply chain. ITRPV estimates bifacial module's world market share will grow from 10% in 2018 to over 60% by 2030.. Industry participants have already demonstrated bifacial energy gain of 5%-33%, depending on module mounting. |
|
Advanced |
Technology Description: Modules maintain historical average of 0.5% improvement per year (25%) -$0.17/W
Justification: Manufactures reported that mass produced cell efficiencies will increase from 20%-23% in 2018 to 21%-24% by 2021. Mass production-monocrystalline and silicon heterojunctionhave already achieved cell efficiency records in a laboratory of 26.1% and 26.7% respectively.
|
Technology Description:Design simplification and manufacturing automation
Justification: power electronics industry already has roadmaps to do simply and automate for current products and there is more potential with increased industry size. |
Technology Description:40% labor cost improvements through automation and pre-assembly efficiencies; the use of low-cost carbon fiber cuts mounting costs
Justification: represents lower levels of improvement than historical average (Feldman et al. Forthcoming). With increased global deployment and more efficient supply chain, pre-assembly is possible. Reduction of supply chain margins (e.g., profit and overhead charged by suppliers, manufacturers, distributors, and retailers), will likely occur naturally as the U.S. PV industry grows and matures. Additionally, streamlining of installation practices through improved workforce development and training and developing standardized PV hardware |
Technology Description: 13% energy gain (10% energy yield gain at module), lower system losses, and degradation rate reduction from 0.7%/yr to 0.2%/yr
Justification: In addition to the justification above, industry participants have already demonstrated bifacial energy gain of 5%-33%, depending on module mounting. |
|
Impact |
Lower module cost, per watt Reductions in PV system labor and BOS material, shipping, and warehousing |
Reduced costs Higher efficiency power conversion |
Lower costs Fewer building errors |
Higher capacity factors |
|
References |
(Fuscher and Bruno 2016; 2016) NREL, "Best Research-Cell Efficiencies (Rev. 04-06-20)" |
Representative Technology
For the 2020 ATB, commercial PV systems are modeled for a 200-kWDC fixed-tilt (5°), roof-mounted system. Flat-plate PV can take advantage of direct and indirect insolation, so PV modules need not directly face and track incident radiation. This gives PV systems a broad geographical application, especially for commercial PV systems.
Distributed-scale PV is assumed to be configured as a fixed-tilt, roof-mounted system. Compared to utility-scale PV, this reduces both the potential capacity factor and amount of land (roof space) that is available for development. A recent study of rooftop PV technical potential (Gagnon et al. 2016) estimated that as much as 731 GW (926 TWh/yr) of potential exists for small buildings (< 5,000 m2 footprint) and 386 GW (506 TWh/yr) for medium (5,000–25,000 m2) and large buildings (> 25,000 m2).
Methodology
This section describes methodology to develop assumptions for CAPEX, O&M, and capacity factor. Click on these links for standardized assumptions for labor cost, regional cost variation, materials cost index, scale of industry, policies and regulations, and inflation.
Currently, CAPEX—not LCOE—is the most common metric for PV cost. Due to differing assumptions in long-term incentives, system location and production characteristics, and cost of capital, LCOE can be confusing and often incomparable for different estimates. While CAPEX also has many assumptions and interpretations, it involves fewer variables to manage. Therefore, PV projections in the 2020 ATB are driven entirely by plant and operational 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 five representative locations in the United States.
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:
- Conservative Scenario: lower levels of R&D investment with minimal technology advancement and current global module pricing
- Moderate Scenario: assume R&D investment continuing at similar levels as today, with no substantial innovations or new technologies introduced to the market
- Advanced Scenario: an increase in R&D spending that generates substantial innovation, allowing historical rates of development to continue.
Capital Expenditures (CAPEX)
Definition: Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year. For commercial PV, this is modeled for only a host-owned business model with access to debt.
For the 2020 ATB, and based on EIA (2016b) and the NREL Solar-PV Cost Model (Feldman et al. Forthcoming) (Barbose and Darghouth 2018), the distributed solar PV plant envelope is defined to include items noted in the table above.
Base Year: In the chart below, reported historical commercial-scale PV installation CAPEX (Barbose and Darghouth 2018) is shown in box-and-whiskers format for comparison to historical commercial-scale PV benchmark overnight capital cost and ATB future CAPEX projections. The data in Barbose and Darghouth (2018) represent 81% of all U.S. residential PV and commercial PV capacity installed through 2018 and 76% of capacity installed in 2018.
The difference in each year's price between the market and benchmark data reflects differences in methodologies. Reported and benchmark prices can differ for a variety of reasons, as enumerated by Barbose and Darghouth (2018) and Bolinger, Seel, and Robson (2018), including:
- Timing-related issues: For instance, the time between contract completion and project placement in service may vary.
- Variations over time in the size, technology, installer margin, and design of systems installed in a given year
- 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, and these included costs may have otherwise been reported as operating costs. The bottom-up benchmarks are more reflective of an overnight capital cost, which is in line with the ATB methodology of inputting overnight capital cost 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. For commercial PV, this would correspond to the combined rated capacity of all inverters. This is because kWDC is the unit that the majority of the PV industry uses. 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 2019 reflect continued rapid decline in pricing supported by analysis of recent system pricing for projects that became operational in 2019 (Feldman et al. Forthcoming).
The historical chart above shows the range in historical CAPEX that reflects the heterogeneous composition of the commercial PV market in the United States.
The chart also 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 innovations scenario. Additionally, commercial PV CAPEX does not correlate well with solar resource.
Although the technology market share may shift over time with new developments, the typical installation cost is represented with the projections above.
System prices of $2.00/WDC in 2018 and $1.77/WDC in 2019 are based on bottom-up benchmark analysis reported in U.S. Solar Photovoltaic System Cost Benchmark Q1 2019 (Feldman et al. Forthcoming), adjusted for inflation. The 2018 and 2019 bottom-up benchmarks are reflective of an overnight capital cost, which is in line with the ATB methodology of inputting overnight capital cost and calculating construction financing to derive CAPEX.
The Base Year CAPEX estimates should tend toward the low end of observed cost because no regional impacts are included. These effects are represented in the historical market data.
Future Years: Projections of 2030 commercial PV plant CAPEX are based on bottom-up cost modeling, with a straight-line change in price in the intermediate years between 2019 and 2030. A summary of the system design and price changes made in the models are described in the Summary of Technology Innovations by Scenario table. See below for the details of changes to components of system price in the different ATB scenarios.
We assume each scenario's 2050 CAPEX is the equivalent of the 2030 CAPEX of the scenario but one degree more aggressive, with a straight-line change in price in the intermediate years between 2030 and 2050. Asterisks indicate corresponding cells, where scenarios use the same values but shifted in time. We also developed and modeled a scenario one degree more aggressive than the Advanced Scenario to estimate its 2050 CAPEX. The 2050 Advances Scenario assumes: a module efficiency of 30%, achieved through double-junction cells (perovskite on top of c-Si); further inverter simplification and manufacturing automation; 50% labor cost improvements through automation and pre-assembly efficiencies; and that low-cost carbon fiber cuts material costs in half.
Year | Advanced (Increased level of R&D) | Moderate (Current level of R&D) | Conservative (Decreased level of R&D) |
2030 | **Commercial PV CAPEX: $0.78/WDC | ***Commercial PV CAPEX: $1.01/WDC | Commercial PV CAPEX: $1.57/WDC |
2050 | *$0.57/WDC | **$0.78/WDC | ***$1.01/WDC |
We compared the CAPEX scenarios over time to four analysts' projections, adjusted for inflation (see chart below). The 2020 ATB CAPEX projections are fairly in-line with other analysts' projections through 2030, with the exception of the analysts' maximum projection, which starts at a much higher CAPEX. Two of the four analyst projections do not go beyond 2030, so there are limited datapoints to compare the ATB projections, however the Advanced Scenario is in-line with the minimum analyst projection.
Use the following table to view the components of CAPEX.
Operation and Maintenance (O&M) Costs
Definition: Operation and maintenance (O&M) costs represent the annual expenditures required to operate and maintain a solar PV plant over its lifetime, including items noted in the table above.
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.
FOM of $18/kWDC – yr is based on modeled pricing for a commercial PV system quoted in 2018 as reported by Feldman et al. (Forthcoming). A wide range in reported prices exists in the market, which in part depend on the maintenance practices that exist for a particular system. These cost categories include asset management (including compliance and reporting for incentive payments), different insurance products, site security, cleaning, vegetation removal, and component failure. Not all these practices are performed for each system; additionally, some factors depend on the quality of the parts and construction. NREL analysts estimate O&M costs can range from $0 to $40/kWDC – yr.
Future Year: FOM for 2019 is also based on pricing reported by Feldman et al. (Forthcoming), adjusted for inflation. From 2020 to 2050, FOM is based on the historical average ratio of O&M costs ($/kW-yr) to CAPEX costs ($/kW), 0.7:100, as reported by Feldman et al. (Forthcoming). Historically reported data suggest O&M and CAPEX cost reductions are correlated; from 2010 to 2019, benchmark commercial PV O&M and CAPEX costs fell 62% and 68% respectively, as reported by Feldman et al. (Forthcoming).
Use the following table to view the components of O&M.
Capacity Factor
Definition: Commercial PV system capacity 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 2020 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), the bifaciality of the module, shading, expected downtime, and inverter losses to transform from DC to AC power. The DC-to-AC ratio is a design choice that influences the capacity factor. PV plant capacity factor incorporates an assumed degradation rate of 0.7%/yr (Feldman et al. Forthcoming) in the annual average calculation. R&D could increase energy yield through bifaciality, better soil removal, improved cell temperature, lower system losses, O&M practices that improve uptime, and lower degradation rates of PV plant capacity factor; future projections assume energy yield gains of 0%–25% depending on the location and scenario For the 2020 ATB, commercial PV systems are modeled for a 200-kWDC fixed-tilt (5°), roof-mounted system.
Base Year: Click here and select Tech Detail = All to add filters to the initial figure on this page to show a range of capacity factors based on variation in solar resource in the contiguous United States. The range of the Base Year estimates illustrate the effect of locating a utility-scale PV plant in places with lower or higher solar irradiance. These five values use specific locations as examples of high (Daggett, California), high-mid (Los Angeles, California), mid (Kansas City, Missouri), low-mid (Chicago, Illinois), and low (Seattle, Washington) resource areas in the United States as implemented in the System Advisor Model using PV system characteristics from Fu, Feldman, and Margolis (2018).
Solar resources in the 2020 ATB are categorized according to the range of solar irradiance across the range of latitudes for five resource locations in the contiguous United States:
- Low: Seattle, Washington
- Low-mid: Chicago, Illinois
- Mid: Kansas City, Missouri
- High-mid: Los Angeles, California
- High: Daggett, California.
First-year operation capacity factors as modeled range from 13.2% to 20.6%, though these depend significantly on location and system configuration (e.g., fixed-tilt or single-axis tracking).
Over time, PV installation output is reduced due to 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 2020 ATB Base Year are 12.9% (Seattle, WA), 14.4% (Chicago, IL), 15.4% (Kansas City, MO), 18.0% (Los Angeles, CA), and 19.5% (Daggett, CA).
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, reduced system losses, and a straight-line reduction in PV plant capacity degradation rates from 0.7%/yr that reach 0.5%/yr, and 0.2%/yr by 2030 for the moderate and advanced technology innovation scenarios respectively. The conservative technology innovation scenario assumes no improvement in degradation rates through 2030. The following table summarizes the difference in average capacity factor in 2030 caused by these changes in the technology innovation scenarios. Similar to our CAPEX assumptions, we assume each scenario's 2050 capacity factor is the equivalent of the 2030 capacity factor of the scenario but one degree more aggressive, with a straight-line change in price in the intermediate years between 2030 and 2050.
Seattle, WA | Chicago, IL | Kansas City, MO | Los Angeles, CA | Daggett, CA | |
Advanced Scenario | 14.7% | 17.0% | 18.2% | 21.2% | 22.9% |
Moderate Scenario | 13.5% | 15.6% | 16.6% | 19.4% | 21.0% |
Conservative Scenario | 12.4% | 14.4% | 15.4% | 18.0% | 19.5% |
We also developed and modeled a scenario one degree more aggressive than the Advanced Scenario to estimate its 2050 capacity factor. The 2050 Advances Scenario assumes: 23%-25% energy gain, depending on location, through a 20% energy yield gain at the module and lower system losses; and a 0.2%/year degradation rate. This is achieved through bifaciality, soil removal, improved cell temperature, and improved O&M uptime.
References
The following references are specific to this page; for all references in this ATB, see References.
Barbose, Galen, & Darghouth, Naïm. (2019). Tracking the Sun: Pricing and Design Trends for Distributed Photovoltaic Systems in the United States: Tracking the Sun. Lawrence Berkeley National Laboratory. https://emp.lbl.gov/sites/default/files/tracking_the_sun_2019_report.pdf
Barbose, Galen, & Dargouth, Naïm. (2018). Tracking the Sun XI: The Installed Price of Residential and Non-Residential Photovoltaic Systems in the United States. (No. LBNL-2001062). Lawrence Berkeley National Laboratory. https://eta-publications.lbl.gov/sites/default/files/tracking_the_sun_2018_edition_final.pdf
BNEF (2019). 2H 2019 US PV Market Outlook. BNEF (Bloomberg New Energy Finance).
BNEF (2019). New Energy Outlook 2019. https://about.bnef.com/new-energy-outlook/
Bolinger, Mark, & Seel, Joachim. (2018). Utility-Scale Solar: An Empirical Trends in Project Technology, Cost, Performance, and PPA Pricing in the United States (2018 Edition). Lawrence Berkeley National Laboratory. https://emp.lbl.gov/sites/default/files/lbnl_utility_scale_solar_2018_edition_report.pdf
EIA (2016). Capital Cost Estimates for Utility Scale Electricity Generating Plants. U.S. Energy Information Administration. https://www.eia.gov/analysis/studies/powerplants/capitalcost/pdf/capcost_assumption.pdf
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.
Fu, Ran, Feldman, David, & Margolis, Robert. (2018). U.S. Solar Photovoltaic System Cost Benchmark: Q1 2018. National Renewable Energy Laboratory. https://www.nrel.gov/docs/fy19osti/72399.pdf
Fuscher, Moritz, & Bruno, Ehrler. (2016). Efficiency Limit of Perovskite/Si Tandem Solar Cells. ACS Energy Lett., 1(4), 863–868.
Gagnon, Pieter, Margolis, Robert, Melius, Jennifer, Phillips, Caleb, & Elmore, Ryan. (2016). Rooftop Solar Photovoltaic Technical Potential in the United States: A Detailed Assessment. (No. NREL/TP-6A20-65298). National Renewable Energy Laboratory. https://www.nrel.gov/docs/fy16osti/65298.pdf
ITRPV (n.d.). International Technology Roadmap for Photovoltaic (ITRPV). International Technology Roadmap for Photovoltaic (ITRPV) i. https://itrpv.vdma.org/
Satpathy, Rabindra (n.d.). Additional Energy Yield Using Bifacial Solar PV Modules and Dependency on Albedo. https://www.ises.org/sites/default/files/webinars/Presentation Rabi Satpathy_ISESWebinar_0.pdf
Wood Mackenzie (2019). U.S. PV System Pricing H2 2019: System Pricing, Breakdowns and Forecasts. https://www.woodmac.com/reports/power-markets-us-solar-pv-system-pricing-h2-2019-361390
Developed with funding from the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy.