Pumped Storage Hydropower

The 2022 ATB data for pumped storage hydropower (PSH) are shown above. Base Year capital costs and resource characterizations are taken from a national closed-loop PSH resource assessment completed under the U.S. Department of Energy (DOE) HydroWIRES Project D1: Improving Hydropower and PSH Representations in Capacity Expansion Models. Resource assessment and cost assumptions are documented by (Rosenlieb et al., 2022). This effort considered only closed-loop systems due to their relatively lower environmental impacts, so open-loop and other configurations are not included in these estimates. Operation and maintenance O&M costs and round-trip efficiency are based on estimates for a 1,000-MW system reported in the 2020 DOE Grid Energy Storage Technology Cost and Performance Assessment. (Mongird et al., 2020). Projected changes in capital costs are based on the DOE Hydropower Vision study (DOE, 2016) and assume different degrees of technology improvement and technological learning.

The three scenarios for technology innovation are:

Conservative Technology Innovation Scenario (Conservative Scenario): no change from baseline CAPEX and O&M costs through 2050
Moderate Technology Innovation Scenario (Moderate Scenario): no change from baseline CAPEX and O&M costs through 2050, consistent with the Reference case in the DOE Hydropower Vision study (DOE, 2016)
Advanced Technology Innovation Scenario (Advanced Scenario): CAPEX reductions of 12% by 2050 based on improved process and design improvements along with advanced manufacturing, new materials, and other technology improvements, consistent with Advanced Technology in the DOE Hydropower Vision study (DOE, 2016); no changes to O&M.

Resource Categorization

Resource categorization from a national closed-loop PSH resource assessment is described in detail by (Rosenlieb et al., 2022). Individual sites are identified using geospatial algorithms to delineate potential reservoir boundaries, exclude reservoirs that violate technical potential criteria (e.g., protected land, critical habitat), find all possible reservoir pairings, and then eliminate overlapping reservoirs to produce the least-cost set of non-overlapping reservoir pairs. Underlying data are site-specific, but for the ATB, resource classes are binned by capital cost such that each class contains a roughly equal amount of total national PSH capacity potential. Binning is done at the national level for the data tables below, and other representations use region-specific cost bins to better represent the distribution of site characteristics in each region. Physical characteristics and capital cost statistics for each ATB class are included in the table below.

Resource Class Capacity and Capital Costs

ATB Class	Total Number of Sites Identified	Total Generating Capacity (GW)	Site Generating Capacity (MW)			Capital Cost (2020$/kW)
ATB Class	Total Number of Sites Identified	Total Generating Capacity (GW)	Average	Min	Max	Average	Min	Max
Class 1	340	189	557	182	3,328	$1,912	$1,200	$2,138
Class 2	472	188	397	163	1,500	$2,292	$2,138	$2,416
Class 3	523	188	359	153	1,382	$2,526	$2,416	$2,620
Class 4	629	188	298	138	959	$2,729	$2,621	$2,831
Class 5	653	187	286	120	1,028	$2,923	$2,831	$3,006
Class 6	736	188	256	106	1,036	$3,089	$3,006	$3,171
Class 7	760	187	247	101	1,203	$3,256	$3,171	$3,341
Class 8	810	187	231	105	965	$3,423	$3,341	$3,501
Class 9	874	187	214	87	790	$3,584	$3,501	$3,667
Class 10	927	187	202	90	1,028	$3,755	$3,667	$3,839
Class 11	960	188	195	82	1011	$3,931	$3,839	$4,023
Class 12	1,001	187	187	89	811	$4,123	$4,023	$4,232
Class 13	1,071	188	175	82	720	$4,357	$4,233	$4,486
Class 14	1,069	187	175	71	609	$4,654	$4,486	$4,850
Class 15	944	188	199	67	619	$5,266	$4,850	$6,981
Totals	11,769	2,814

Resource Class Design Values

ATB Class	Reservoir Volume (gigaliters)			Hydraulic Head (m)			Distance Between Reservoirs (m)
ATB Class	Average	Min	Max	Average	Min	Max	Average	Min	Max
Class 1	4.3	1.0	43.5	693	332	1531	3,700	1184	4498
Class 2	3.6	1.3	20.6	585	300	940	3,695	1342	4497
Class 3	3.6	1.4	21.6	520	300	800	3,678	994	4498
Class 4	3.2	1.3	15.0	480	300	751	3,649	1080	4499
Class 5	3.3	1.3	16.1	442	300	669	3,648	674	4497
Class 6	3.1	1.2	15.1	418	300	624	3,647	713	4497
Class 7	3.1	1.2	17.6	400	300	566	3,640	811	4498
Class 8	3.0	1.2	14.1	378	300	592	3,645	700	4497
Class 9	2.9	1.0	12.7	369	300	553	3,682	560	4499
Class 10	2.8	1.1	16.0	355	300	510	3,673	780	4499
Class 11	2.7	1.1	14.4	346	300	510	3,705	966	4499
Class 12	2.7	1.2	13.1	335	300	498	3,765	661	4499
Class 13	2.6	1.2	11.6	327	300	471	3,815	911	4499
Class 14	2.7	1.1	9.8	319	300	469	3,898	1128	4499
Class 15	3.1	1.1	9.1	312	300	430	3,980	1860	4499

Scenario Descriptions

Cost reductions in the Advanced Scenario reflect various types of technology innovations that could be applied to PSH facilities. These potential innovations, which are discussed in the DOE Hydropower Vision Roadmap (DOE, 2016), are largely similar to technology pathways for hydropower without pumping.

Summary of Technology Innovation: Advanced Scenario

	Modularity	New Materials	Eco-Friendly Pumps and Turbines	Innovative Closed-Loop Concepts
Technology Descriptions	Drop-in systems that minimize civil works and maximize ease of manufacture	Alternative materials for water diversion (e.g., penstocks)	Innovative approaches to improved environmental performance	Off-river designs allowing better combined economic and environmental performance
Impacts	Reduced civil works cost	Reduced construction material costs	Reduced environmental mitigation costs	Reduced environmental costs and increased modularity and standardization
References	(DOE, 2016)	(DOE, 2016)	(DOE, 2016)	(DOE, 2016)

Representative Technology

The resource assessment procedure requires several design specifications to be defined up front, and for the resource included in the ATB, these include a fixed 30-m dam height, a minimum 300-m hydraulic head height, and a maximum reservoir distance of 15 times the head height (Rosenlieb et al., 2022). Upper and lower reservoir volumes are also assumed to be within 20% of each other. Given the resulting technical specifications of each reservoir pair, the powerhouse (turbine, generator, and electrical equipment) can be sized flexibly for a given reservoir pair, and here all data assume the powerhouse is sized for exactly 10 hours of storage duration (i.e., a maximum of 10 hours generating at rated capacity).

Methodology

This section describes the methodology to develop assumptions for CAPEX, O&M, and round-trip efficiency.

Capital Expenditures (CAPEX)

Capital costs are first calculated for each site using the PSH cost model from Australia National University (Andrew Blakers et al., 2019) adjusted to use a 33% project contingency factor instead of the base 20% assumption to better align with other technologies and U.S. industry practice. The cost model uses reservoir and powerhouse characteristics as inputs to generalized equations for PSH overnight capital cost. These raw costs are then further calibrated to more closely match hydropower industry expectations by multiplying site costs by a factor equal to the ratio of the central CAPEX estimate in (Mongird et al., 2020) for a 1,000-MW, 10-hour facility to the median CAPEX of all sites in the capacity range of 900–1,100 MW (Mongird et al., 2020). This factor is equal to 1.51, and due to the limited amount of available cost data, this factor is applied uniformly to all sites. Grid connection costs are then added based on the distance from the powerhouse location (assumed at the lower reservoir) to the nearest high-voltage transmission line node (Maclaurin et al., 2021). Cost assessment is described in greater detail in (Rosenlieb et al., 2022).

The maps below plot median CAPEX in each state for each of 15 resource classes when individual sites are binned by cost separately for each state. Some states have zero sites identified, largely due to insufficient elevation differences to meet a 300 m minimum head height criteria. The ratio of distance between reservoirs to head height (L/H ratio) is also shown for individual sites. The display also includes links to a bar chart and a tabular display. The bar chart shows more granular data for each balancing area defined in the Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al., 2021) along with the state average PSH capital cost. The table allows the data to be filtered by class and balancing area to view region- or class-specific data.

Regional PSH Capital Cost by Class

Operation and Maintenance (O&M) Costs

(Mongird et al., 2020) characterize PSH O&M costs using a literature review of recently published sources of PSH cost and performance data. For the 2022 ATB, we use cost estimates for a 1,000-MW plant, which has lower labor costs per power output capacity than a smaller facility. O&M costs also include component costs for standard maintenance, refurbishment, and repair. O&M cost reductions are not projected because the relevant technical components are assumed to be mature, so they are constant and identical across all scenarios.

Round-Trip Efficiency

Round-trip efficiency is also based on a literature review by (Mongird et al., 2020), who report a range of 70%–87% across several sources. The value of 80% is taken as a central estimate, and no improvements are projected either in (Mongird et al., 2020) or here because the relevant technical components are assumed to be mature. Thus, round-trip efficiency is constant and identical across all scenarios.

References

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

Rosenlieb, Evan, Donna Heimiller, and Stuart Cohen. “Closed-Loop Pumped Storage Hydropower Resource Assessment for the United States.” Golden, CO: National Renewable Energy Laboratory, 2022. https://www.nrel.gov/docs/fy22osti/81277.pdf.

Mongird, Kendall, Vilayanur Viswanathan, Jan Alam, Charlie Vartanian, Vincent Sprenkle, and Richard Baxter. “2020 Grid Energy Storage Technology Cost and Performance Assessment.” Washington, D.C.: U. S. Department of Energy, December 2020. https://www.energy.gov/energy-storage-grand-challenge/downloads/2020-grid-energy-storage-technology-cost-and-performance.

DOE. “Hydropower Vision: A New Chapter for America’s Renewable Electricity Source.” Washington, D.C.: U.S. Department of Energy, 2016. https://doi.org/10.2172/1502612.

Maclaurin, Galen, Nicholas Grue, Anthony Lopez, Donna Heimiller, Michael Rossol, Grant Buster, and Travis Williams. “The Renewable Energy Potential (ReV) Model: A Geospatial Platform for Technical Potential and Supply Curve Modeling.” Golden, CO: National Renewable Energy Laboratory, 2021. https://doi.org/10.2172/1563140.

Ho, Jonathan, Jonathon Becker, Maxwell Brown, Patrick Brown, Ilya (ORCID:0000000284917814) Chernyakhovskiy, Stuart Cohen, Wesley (ORCID:000000029194065X) Cole, et al. “Regional Energy Deployment System (ReEDS) Model Documentation: Version 2020.” Golden, CO: National Renewable Energy Laboratory, June 9, 2021. https://doi.org/10.2172/1788425.

Andrew Blakers, Matthew Stocks, Bin Lu, Kirsten Anderson, and Anna Nadolny. “Global Pumped Hydro Atlas.” Australian National University, 2019. http://re100.eng.anu.edu.au/research/phes/.