2019 ATB
For each electricity generation technology in the ATB, this website provides:
- Capital expenditures (CAPEX): the definition of CAPEX used in the ATB and the historical trends, current estimates, and future projections of CAPEX used in the ATB
- Operations and maintenance (O&M) costs: the definition of O&M and the current estimates and future projections of O&M used in the ATB
- Capacity factor (CF): the definition of CF and the historical trends, current estimates, and future projections of CF used in the ATB
- Future cost and performance methods: an outline of the methodology used to make the projections of future cost and performance in the ATB for Constant, Mid, and Low technology cost cases
- Levelized cost of energy (LCOE): metric that combines CAPEX, O&M, CF, and projections for Constant, Mid, and Low technology cost cases for illustration of the combined effect of the primary cost and performance components and discussion of technology advances that yield future projections
- Financing assumptions: development of technology-specific interest rate on debt, return on equity, and debt-to-equity ratios and their impact on LCOE are documented in each technology section, where applicable, and summarized here.
Electricity generation technologies are selected on the left side of the screen, and the topics highlighted above can be selected using the drop-down menu at the top right of the screen.
Guidelines for using and interpreting ATB content and comparisons to other literature are provided. LCOE accounts for many variables important to determining the competitiveness of building and operating a specific technology (e.g., upfront capital costs, capacity factor, and cost of financing); however, it does not necessarily demonstrate which technology in a given place and time would provide the lowest cost option for the electricity grid. Such analysis is performed using electric sector models such as the Regional Energy Deployment Systems (ReEDS) model and corresponding analysis results such as the NREL Standard Scenarios.
The NREL Standard Scenarios, a companion product to the ATB, provides a suite of electric sector scenarios and associated assumptions, including technology cost and performance assumptions from the ATB.
ATB data sources and references are also provided for each technology. All dollar values are presented in 2017 U.S. dollars, unless noted otherwise.
Additional information is available here: About the 2019 ATB.
Battery Storage
Energy storage technologies are important to document in the ATB because of their potential role in enhancing grid flexibility, especially under scenarios of high penetration of variable renewable technologies. CSP with TES and Hydropower both include storage capabilities, and a variety of other storage technologies could enhance the flexibility of the electrical grid. This section documents assumptions about only one of them: 4-hour, utility-scale, lithium-ion battery storage. NREL has completed recent analysis on ranges of costs related to other battery sizes (Fu, Remo, & Margolis, 2018) with relative costs represented in Figure ES-1 of the report (included below) which looked at 4-hour to 0.5 hour battery duration of utility scale plants.
The ATB does not currently have costs for distributed battery storage-either for residential nor commercial applications behind the meter nor for a micro-grid or off-grid application. NREL has completed prior work on residential battery plus solar PV system analysis (Ardani et al., 2017) resulting in a range of costs of PV+battery systems as shown in the figure below. Note these costs are for 2016 and published in 2017, so we anticipate battery costs to be significantly lower currently.
Base Year and Future Year Projections Overview
Battery cost and performance projections are based on a literature review of 25 sources published between 2016 and 2019, as described by Cole and Frazier (2019) . Three different projections from 2017 to 2050 were developed for scenario modeling based on this literature:
- High Technology Cost Scenario: generally based on the maximum of literature projections of future CAPEX and O&M technology pathway analysis; distinct from the Constant technology cost scenarios used among renewable energy technologies in the ATB
- Mid Technology Cost Scenario: generally based on the median of literature projections of future CAPEX and O&M technology pathway analysis
- Low Technology Cost Scenario: generally based on the low bound of literature projections of future CAPEX and O&M technology pathway analysis.
Standard Scenarios Model Results
ATB CAPEX, O&M, and round-trip efficiency assumptions for the Base Year and future projections through 2050 for High, Mid, and Low technology cost scenarios are used to develop the NREL Standard Scenarios using the ReEDS model. See ATB and Standard Scenarios.
Representative Technology
The representative technology was a utility-scale lithium-ion battery storage system with a 15-year life and a 4-hour rating, meaning it could discharge at its rated capacity for four hours as described by Cole and Frazier (2019) . Within the ATB spreadsheet, the costs are separated into energy and power cost estimates, which allow capital costs to be constructed for durations other than 4 hours according to the following equation:
For more information on the power vs. energy cost breakdown, see Cole and Frazier (2019) .
Capital Expenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections
Recent Trends
Costs of lithium-ion battery storage systems have declined rapidly in recent years, prompting greater interest in utility-scale applications.
Base Year Estimates
The Base Year cost estimate is taken from Fu, Remo, and Margolis (2018). Comparisons to other reported costs for 2018 are included in Cole, Wesley & Frazier, A. Will (2019). Although the ATB uses a 2017 Base Year, the 2018 estimate based on the literature is the first year reported in the ATB, with a value of $1,484/kW in 2017 dollars.
Future Projections
Future projections are taken from Cole and Frazier (2019), which generally used the median of published cost estimates to develop a Mid Technology Cost Scenario and the minimum values to develop a Low Technology Cost Scenario. Analysts' judgment was used to select the long-term projections to 2050 from a sparse data set.
CAPEX Definition
The literature review does not enumerate elements of the capital cost of lithium-ion batteries (Cole, Wesley & Frazier, A. Will, 2019). However, the NREL storage cost report does detail a breakdown of capital costs with the actual battery pack being the largest component but significant other costs are also included. This breakdown is different if the battery is part of a hybrid system with solar PV. These relative costs for utility-scale standalone battery and battery + PV are demonstrated in the figure below (Fu, Remo, & Margolis, 2018).
Operation and Maintenance (O&M) Costs
Base Year Estimates
Cole and Frazier (2019) assumed no variable operation and maintenance (VOM) cost. All operating costs were instead represented using fixed operation and maintenance (FOM) costs. The FOM costs include augmentation costs needed to keep the battery system operating at rated capacity for its lifetime. In the ATB, FOM is defined as the value needed to compensate for degradation to enable the battery system to have a constant capacity throughout its life. The literature review states that FOM costs are estimated at 2.5% of the $/kW capital costs.
Future Projections
In the ATB, the FOM cost remains constant at 2.5% of capital costs in all scenarios.
Round-trip efficiency is the ratio of useful energy output to useful energy input. Cole and Frazier (2019) identified 85% as a representative round-trip efficiency, and the ATB adopts this value.
Biopower
The ATB includes both dedicated biopower cost options and a biomass cofired with coal option. The cost and performance characteristics of these plants are adapted from EIA data rather than derived from original analysis.
Capital Expenditures (CAPEX): Historical Trends, Current Estimates, and Future Projections
Biopower plant CAPEX is taken from the AEO2019 Reference Scenario (EIA, 2019a) with the adjustments discussed in the CAPEX definition section.
CAPEX Definition
Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.
Overnight capital costs are modified from AEO2019 (EIA, 2019a). The EIA projections were adjusted by removing the material price index. The material price index accounts for projected changes in the price index for metals and metals products, and it is independent of the learning-based cost reductions applied in the EIA projections.
Fuel costs are taken from the Billion Ton Update study (DOE et al., 2011).
| Overnight Capital Cost ($/kW) | Construction Financing Factor (ConFinFactor) | CAPEX ($/kW) | |
| Dedicated: Dedicated biopower plant | $3,827 | 1.042 | $3,990 |
| CofireOld: Pulverized coal with sulfur dioxide (SO2) scrubbers and biomass co-firing | $4,013 | 1.042 | $4,184 |
| CofireNew: Advanced supercritical coal with SO2 and NOx controls and biomass co-firing | $4,013 | 1.042 | $4,184 |
CAPEX can be determined for a plant in a specific geographic location as follows:
Regional cost variations and geographically specific grid connection costs are not included in the ATB (CapRegMult = 1; GCC = 0). In the ATB, the input value is overnight capital cost (OCC) and details to calculate interest during construction (ConFinFactor).
In the ATB, CAPEX represents each type of biopower plant with a unique value. Regional cost effects associated with labor rates, material costs, and other regional effects as defined by (EIA, 2016) expand the range of CAPEX. Unique land-based spur line costs based on distance and transmission line costs are not estimated. The following figure illustrates the ATB representative plant relative to the range of CAPEX including regional costs across the contiguous United States. The ATB representative plants are associated with a regional multiplier of 1.0.
Operation and Maintenance (O&M) Costs
Biopower power plant fixed and variable O&M costs are taken from table 8.2 of the AEO2019, and they are assumed to be constant over time.
Capacity Factor: Expected Annual Average Energy Production Over Lifetime
The capacity factor represents the assumed annual energy production divided by the total possible annual energy production, assuming the plant operates at rated capacity for every hour of the year. For biopower plants, the capacity factors are typically lower than their availability factors. Biopower plant availability factors have a wide range depending on system design, fuel type and availability, and maintenance schedules.
Biopower plants are typically baseload plants with steady capacity factors. For the ATB, the biopower capacity factor is taken as the average capacity factor for biomass plants for 2017, as reported by EIA.
Biopower capacity factors are influenced by technology and feedstock supply, expected downtime, and energy losses.
Levelized Cost of Energy (LCOE) Projections
Levelized cost of energy (LCOE) is a summary metric that combines the primary technology cost and performance parameters: CAPEX, O&M, and capacity factor. It is included in the ATB for illustrative purposes. The ATB focuses on defining the primary cost and performance parameters for use in electric sector modeling or other analysis where more sophisticated comparisons among technologies are made. The LCOE accounts for the energy component of electric system planning and operation. The LCOE uses an annual average capacity factor when spreading costs over the anticipated energy generation. This annual capacity factor ignores specific operating behavior such as ramping, start-up, and shutdown that could be relevant for more detailed evaluations of generator cost and value. Electricity generation technologies have different capabilities to provide such services. For example, wind and PV are primarily energy service providers, while the other electricity generation technologies provide capacity and flexibility services in addition to energy. These capacity and flexibility services are difficult to value and depend strongly on the system in which a new generation plant is introduced. These services are represented in electric sector models such as the ReEDS model and corresponding analysis results such as the Standard Scenarios.
The following three figures illustrate LCOE, which includes the combined impact of CAPEX, O&M, and capacity factor projections for biomass across the range of resources present in the contiguous United States. For the purposes of the ATB, the costs associated with technology and project risk in the U.S. market are represented in the financing costs but not in the upfront capital costs (e.g., developer fees and contingencies). An individual technology may receive more favorable financing terms outside the United States, due to less technology and project risk, caused by more project development experience (e.g., offshore wind in Europe) or more government or market guarantees. The R&D Only LCOE sensitivity cases present the range of LCOE based on financial conditions that are held constant over time unless R&D affects them, and they reflect different levels of technology risk. This case excludes effects of tax reform, tax credits, and changing interest rates over time. The R&D + Market LCOE case adds to these financial assumptions: (1) the changes over time consistent with projections in the Annual Energy Outlook and (2) the effects of tax reform and tax credits. Data for all the resource categories can be found in the ATB data spreadsheet; for simplicity, not all resource categories are shown in the figures.
R&D Only | R&D + Market
The LCOE of biopower plants is directly impacted by the differences in CAPEX (installed capacity costs) as well as by heat rate differences. For a given year, the LCOE assumes that the fuel prices from that year continue throughout the lifetime of the plant.
Regional variations will ultimately impact biomass feedstock costs, but these are not included in the ATB.
The projections do not include any cost of carbon.
Fuel costs are taken from the Billion Ton Update study (DOE et al., 2011).
To estimate LCOE, assumptions about the cost of capital to finance electricity generation projects are required, and the LCOE calculations are sensitive to these financial assumptions. Two project finance structures are used within the ATB:
- R&D Only Financial Assumptions: This sensitivity case allows technology-specific changes to debt interest rates, return on equity rates, and debt fraction to reflect effects of R&D on technological risk perception, but it holds background rates constant at 2017 values from AEO2019 (EIA, 2019a) and excludes effects of tax reform and tax credits. A constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies.
- R&D Only + Market Financial Assumptions: This sensitivity case retains the technology-specific changes to debt interest, return on equity rates, and debt fraction from the R&D Only case and adds in the variation over time consistent with AEO2019 (EIA, 2019a) as well as effects of tax reform and tax credits. As in the R&D Only case, a constant cost recovery period-or period over which the initial capital investment is recovered-of 30 years is assumed for all technologies. For a detailed discussion of these assumptions, see Project Finance Impact on LCOE.
The equations and variables used to estimate LCOE are defined on the Equations and Variables page. For illustration of the impact of changing financial structures such as WACC, see Project Finance Impact on LCOE. For LCOE estimates for the Constant, Mid, and Low technology cost scenarios for all technologies, see 2019 ATB Cost and Performance Summary.
References
The following references are specific to this page; for all references in this ATB, see References.Ardani, K., O'Shaughnessy, E., Fu, R., McClurg, C., Huneycutt, J., & Margolis, R. (2017). Installed Cost Benchmarks and Deployment Barriers for Residential Solar Photovoltaics with Energy Storage: Q1 2016 (No. NREL/TP-7A40-67474). Retrieved from National Renewable Energy Laboratory website: Installed Cost Benchmarks and Deployment Barriers for Residential Solar Photovoltaics with Energy Storage: Q1 2016
Cole, Wesley, & Frazier, A. Will. (2019). Cost Projections for Utility-Scale Battery Storage (No. NREL/TP-6A20-73222). Retrieved from National Renewable Energy Laboratory website: https://www.nrel.gov/docs/fy19osti/73222.pdf
DOE. (2011). U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry (No. ORNL/TM-2011/224). https://doi.org/10.2172/1023318
EIA. (2016b). Capital Cost Estimates for Utility Scale Electricity Generating Plants. Retrieved from U.S. Energy Information Administration website: https://www.eia.gov/analysis/studies/powerplants/capitalcost/pdf/capcost_assumption.pdf
EIA. (2019a). Annual Energy Outlook 2019 with Projections to 2050. Retrieved from U.S. Energy Information Administration website: https://www.eia.gov/outlooks/aeo/pdf/AEO2019.pdf
EIA. (2019b, January). Table 6.7.B Capacity Factors for Utility Scale Generators Not Primarily Using Fossil Fuels. Retrieved April 22, 2019, from https://www.eia.gov/electricity/monthly/epm_table_grapher.php?t=epmt_6_07_b
Fu, R., Remo, T. W., & Margolis, R. M. (2018). 2018 U.S. Utility-Scale Photovoltaics-Plus-Energy Storage System Costs Benchmark (No. NREL/TP-6A20-71714). https://doi.org/10.2172/1483474