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.
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:
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.
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) .
Costs of lithium-ion battery storage systems have declined rapidly in recent years, prompting greater interest in utility-scale applications.
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 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.
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).
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.
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.
The ATB includes three coal power plant types: coal-new, coal-IGCC, and coal-CCS. The cost and performance characteristics of these plants are adapted from EIA data rather than derived from original analysis.
Coal power plant CAPEX is taken from the AEO2019 Reference Scenario (EIA, 2019a) with the adjustments discussed in the CAPEX definition section. The ATB includes only a single CAPEX projection for each type of coal plant.
Lazard (2016) does not explicitly define its ranges with and without CCS; thus, the high end of their pulverized coal and IGCC ranges and the low end of their IGCC-CCS range are assumed to be the middle of the full reported range. All sources have been normalized to the same dollar year. Costs vary due to differences in system design (e.g., coal rank), methodology, and plant cost definitions. The coal capital costs include environmental controls to meet current federal regulations.
Capital expenditures (CAPEX) are expenditures required to achieve commercial operation in a given year.
For coal power plants, CAPEX equals interest during construction (ConFinFactor) times the overnight capital cost (OCC).
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.
For the ATB, coal-CCS technology is ultra-supercritical pulverized coal technology fitted with CCS. Both 30% capture and 90% capture options are included for the coal-CCS technology. The CCS plant configuration includes only the cost of capturing and compressing the CO2. It does not include CO2 delivery and storage.
Overnight Capital Cost ($/kW) | Construction Financing Factor (ConFinFactor) | CAPEX ($/kW) | |
Coal-new: Ultra-supercritical pulverized coal with SO2 and NOx controls | $3,711 | 1.087 | $4,036 |
Coal-IGCC: Integrated gasification combined cycle (IGCC) | $4,055 | 1.087 | $4,409 |
Coal-CCS: Ultra-supercritical pulverized coal with carbon capture and sequestration (CCS) options (30% / 90% capture) | $5,180 / $5,728 | 1.087 | $5,633 / $6,229 |
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 coal 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.
Coal 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.
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 coal plants, the capacity factors are typically lower than their availability factors. Coal plant availability factors have a wide range depending on system design and maintenance schedules.
The capacity factor of dispatchable units is typically a function of the unit's marginal costs and local grid needs (e.g., need for voltage support or limits due to transmission congestion).
Coal power plants have typically been operated as baseload units, although that has changed in many locations due to low natural gas prices and increased penetration of variable renewable technologies. The average capacity factor used in the ATB is the fleet-wide average reported by EIA for 2017. The high capacity factor represents a new plant that would operate as a baseload unit. New coal plants would likely be more efficient than existing coal plants, and therefore would be more likely to be dispatched more often, resulting in capacity factors closer to the "high" level than the "average" level, but actual capacity factors will vary based on local grid conditions and needs.
Even though IGCC and coal with CCS have experienced limited deployment in the United States, it is expected that their performance characteristics would be similar to new coal power plants.
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.
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
Black & Veatch. (2012). Cost and Performance Data for Power Generation Technologies. Retrieved from Black & Veatch Corporation website: https://www.bv.com/docs/reports-studies/nrel-cost-report.pdf
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
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
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
Lazard. (2016). Lazard's Levelized Cost of Energy Analysis: Version 10.0. Retrieved from Lazard website: https://www.lazard.com/media/438038/levelized-cost-of-energy-v100.pdf
Rubin, E. S., Davison, J. E., & Herzog, H. J. (2015). The Cost of CO2 Capture and Storage. International Journal of Greenhouse Gas Control, 40, 378–400. https://doi.org/10.1016/j.ijggc.2015.05.018
Zoelle, A., Keairns, D., Pinkerton, L. L., Turner, M. J., Woods, M., Kuehn, N., … Chou, V. (2015). Cost and Performance Baseline for Fossil Energy Plants Volume 1a: Bituminous Coal (PC) and Natural Gas to Electricity Revision 3 (No. DOE/NETL-2015/1723). https://doi.org/10.2172/1480987