Patrick Balducci, Mark Weimar, Xu Ma, Di Wu, Jonghwan Kwon, Anna Schleifer, Vladimir Koritarov, Sang-il Yim, Bruce Hamilton
The rapidly evolving electricity system with increasing variable renewable energy (VRE) resources provides both opportunities and challenges for the power sector. With the significant ramps and intermittency associated with VRE resources, the requirements and need for additional flexible resources increase. Pumped storage hydropower (PSH) provides flexibility to the electricity grid to replace fossil fuel plants, which are responsible for 25% of U.S. emissions. PSH projects support various aspects of power system operations, including flexibility, ramping capability, energy, ancillary service, black start, and others. The significant potential of hydropower requires understanding the different value drivers to the electricity system specific to the location of a project and then optimizing the plant for the different system values. Thus, determining the value of PSH projects and their many services and contributions to the electricity system can be a challenge for potential developers, system owners, regulators, policy makers, and consultants.
Each storage type has its advantages and disadvantages in the energy storage mix. While the costs and characteristics of energy storage systems vary significantly by site and application, PSH plants typically contain longer-duration energy storage capacity (6–20 h) compared to battery storage (typically fewer than 4 h for lithium-ion batteries), cost less than battery systems per kilowatt-hour of stored energy (US${\$}$263/kWh in energy capacity for a 100-MW 10-h PSH system compared to US${\$}$356.45/kWh for a 100-MW 10-h lithium-iron-phosphate system), and have a life expectancy of up to 100 years compared to 16 years for a lithium-ion system. PSH is the most mature long-duration storage technology. PSH also offers excellent inertial energy due to its rotating turbines and can go from no energy to full capacity in less than 2 min. PSH totaled 553 GWh, or 99%, of U.S. electricity storage capacity in 2019. Despite the considerable advantages of PSH, no new large-scale PSH plants have begun operations in more than 20 years.
Determining the value of a PSH plant has been relatively difficult to date, and without proper economic valuation, the growth of long-duration energy storage will be hindered. The Pumped Storage Hydropower Valuation Tool (PSHVT) seeks to address that problem. The Pumped Storage Hydropower Valuation Guidebook, published by the U.S. Department of Energy (DOE) in 2021, provides a framework for valuing PSH services. The PSHVT, which was sponsored by the DOE’s Water Power Technologies Office (WPTO), is designed to bring that framework to life and to transfer and disseminate PSH valuation guidance to the hydropower industry, PSH developers, and other stakeholders. The PSHVT steps the user through the analysis steps defined in the Guidebook to evaluate a PSH plant and determine its economic feasibility. The PSHVT provides three pathways for assessing the value of PSH operations: 1) a price taker model for small PSH plants (usually less than 10 MW) that will not affect market prices; 2) a price influencer approach that relies on external production cost, capacity expansion, and power flow models that allow prices to adjust along with an integration process to determine the plant benefits from a PSH owner–operator, system or grid operator, and societal perspective; and 3) an embedded price influencer model using the Argonne Low-Carbon Electricity Analysis Framework (A-LEAF) tool that enables the user to evaluate benefits from a PSH owner–operator or system/grid operator perspective. A-LEAF is an integrated national-scale power system simulation framework that includes a suite of capacity expansion, unit commitment, and economic dispatch models. An overview of A-LEAF is presented in the “A-LEAF Price Influencer Tool” section. A screenshot of the PSHVT home page, which can be accessed at https://pshvt.egs.anl.gov, appears in Figure 1. Access to the PSHVT is unrestricted and provided at no cost to the user.
The DOE recently took an additional step to support PSH development in the United States when it established the US${\$}$4.3 million Hydropower and Water Innovation for a Resilient Electricity System (HydroWIRES) technical assistance (TA) program. The purpose of the DOE-funded TA program is to leverage the National Laboratories’ valuable expertise and capabilities to aid stakeholders in making well-informed decisions to improve hydropower’s role in existing or planned systems while achieving broader benefits for the grid. The DOE selected 10 TA projects, with budgets ranging between US${\$}$100,000 and US${\$}$1 million. DOE funding will support TA teams consisting of subject matter experts from one or more of the following DOE National Laboratories: Argonne National Laboratory, Idaho National Laboratory (INL), National Renewable Energy Laboratory, Oak Ridge National Laboratory, and Pacific Northwest National Laboratory (PNNL). An overview of the TA program and links to program material are available at https://pshvt.egs.anl.gov/ta.
PSH is a type of hydroelectric energy storage. Constructed with two water reservoirs at different elevations, it provides long-duration energy storage capability by pumping large quantities of water from a lower elevation to a higher elevation, thereby converting kinetic energy into stored potential energy. Electric power can be generated as water moves down to the lower reservoir, passing through a turbine. PSH plants are characterized as open loop and closed loop. An open-loop facility has a natural source of water flowing into the system, whereas a closed-loop facility is fully isolated from a natural body of water.
There are three major PSH types: reversible, ternary, and separate pumps and turbines. Each type provides a different set of generation and pumping profiles. A reversible unit consists of a pump/turbine and a synchronous motor/generator connected to a single shaft. A ternary unit involves a synchronous motor/generator, a turbine, and a pump coupled on a single shaft. The pump and turbine rotate in the same direction, and flows from the pump can be routed through the turbine, resulting in a hydraulic short circuit (HSC). For both reversible and ternary units, the pump operates at a fixed speed. Being mechanically uncoupled, separate pumps and turbines have the advantage of using different combinations of pump ratings and turbine ratings for different operating scenarios. Adjustable-speed operation allows the pump/motor to operate at a nonsynchronous speed, increasing the range of the power input while pumping. An HSC allows the inlets of turbines and discharges of pumps for all units, regardless of the technology selected, to be connected. An HSC at either a unit or plant level helps increase the flexibility of PSH operation. The price taker model embedded in the PSHVT considers these detailed characteristics in its optimization process, while A-LEAF considers only broad operational parameters, such as the generator and pump minimum/maximum, round-trip efficiency, and energy storage capacity.
Traditionally, PSH plants provide energy arbitrage services—pumping to store energy in the form of water storage during off-peak hours and generating during peak hours. Ancillary services markets, particularly those related to power balancing and frequency regulation, have emerged as an important grid service and value stream. Exploring additional grid/end-user applications from PSH becomes highly important to solve a multitude of issues in today’s rapidly evolving power grid and future decarbonized energy systems, such as resource adequacy, reliability, resilience, and flexibility requirements.
The PSHVT is a step-by-step tool designed to assess the value of services provided by PSH plants as defined in the voluminous Pumped Storage Hydropower Valuation Guidebook. The PSHVT provides an easy-to-follow step-by-step process to work through the Guidebook’s 15-step decision framework. This decision tree-based tool provides valuation guidance for PSH developers, plant owners or operators, and other stakeholders, such as regulators, policy makers, and consultants, to assess the value of existing or potential PSH plants and their services.
The tool is designed to advance the state of the art in assessing the value of a broad range of services provided by PSH plants, including:
The tool enables the user to design multiple projects and several scenarios that fall under each project, where the user can modify inputs and evaluate the sensitivity of the results with respect to changes in those key parameters. For example, a user could evaluate two PSH projects and then save multiple cases under each, where the scale of the plants or key policy assumptions or growth rates are varied. The user can accumulate projects and cases and edit or remove them at his or her discretion. This function enables the user to return to existing cases and update them as needed over time, without having to start from scratch. Note that the number of cases under each project is identified in the repository, and once an individual project is selected, the tool identifies the number of steps completed under each case.
Features of the PSHVT include embedded tools: a back-end benefit–cost analysis (BCA) tool, a price taker valuation tool for small-scale PSH, the A-LEAF tool, and a multi-criteria decision analysis (MCDA) tool. To determine whether the analyst should use the price taker tool or the price influencer approach, one can evaluate whether a PSH plant influences the market by using the Herfindahl–Hirschman Index (HHI). The HHI is the sum of the squares of each market participant’s percentage for a specific market. According to the U.S. Department of Justice and the U.S. Federal Trade Commission, a PSH plant can impact market prices if its addition increases the HHI by more than 100. When evaluating large-scale PSH that could influence market prices, one path of the tool walks the user through a valuation process using capacity expansion planning and production cost models, such as Aurora or PLEXOS. It provides an overview of multiple model types, segmented by primary application, but all calculations are conducted external to the PSHVT. The second price influencer path directs the user to the A-LEAF tool, which enables the user to perform all required calculations to estimate the benefits of PSH operations from a PSH owner–operator or system/grid operator perspective. A recent addition is a downloadable version of the tool.
The PSH valuation framework consists of 15 steps (illustrated in Figure 2) that are grouped into four main activities: define scope, develop valuation criteria, design analysis, and determine and evaluate results. This framework was developed and published in the Pumped Storage Hydropower Valuation Guidebook. Data input in each step (e.g., system information in step 1) are stored and later used to perform calculations in latter steps (e.g., step 12) or to update the report delivered in step 15. Based on the data entered in some steps, users may be directed to go back and revisit previous steps, as shown by the feedback loops on the right-hand side of Figure 2.
The PSH valuation framework used in this tool utilizes a traditional BCA approach to compare the expected cost and benefit streams over the economic life of a PSH plant. In addition, if nonmonetized project impacts also need to be taken into consideration, the tool presents an MCDA approach that can be used to compare different alternatives, described with both monetized and nonmonetized attributes, and explore the tradeoffs among the different attributes. Major elements of the framework are outlined in the following:
Note that user progress is tracked along the left-hand side of the tool. The step the user is working in is highlighted in the tool. Once a step is completed, it remains highlighted, and the circle around the step number turns green. This approach ensures that the user always knows where he or she is in the 15-step process.
The PSHVT relies on user-defined data to determine the PSH plant characteristics and valuation questions and to provide all inputs necessary to run the embedded price taker, price influencer, MCDA, and BCA models. Throughout the 15-step process, the decision tree-based method guides the user through the data acquisition process. Key data elements required to perform all necessary calculations are defined in Table 1.
Table 1. The data required to run the PSHVT.
On each page, the PSHVT provides a definition of each data requirement on the left-hand side of the page and input windows to the right. The units of measure are defined above each input box. Asterisks on the page identify input required to move to the next step.
The price taker framework employed in the PSHVT is designed to evaluate a small closed-loop PSH plant (usually less than 10 MW), where the addition of the plant has little impact on market clearing prices and system-level dispatch when it is used for grid/behind-the-meter (BTM) applications. The price taker framework requires an understanding of which PSH configuration is being analyzed. Specifically, the price taker tool can evaluate three different types of pumped storage, including reversible, ternary, and separate pumps and turbines. Each type of PSH provides a different set of pumping and generating constraints, which the price taker model uses to estimate the value of the services provided. In addition, the price taker has additional features to model adjustable-speed operation as well as unit- and plant-level HSCs.
To meet the challenges of the energy arbitrage and ancillary service markets, the price taker model considers a broad range of grid services, such as energy arbitrage, frequency regulation, spinning reserve, capacity value, critical infrastructure upgrade deferral, and voltage support, using fixed prices based on historical information. The price taker model can also evaluate benefits from BTM use cases for smaller PSH facilities (e.g., inline generation for irrigation systems). Examples of BTM services include power reliability, time-of-use charge management, and demand charge management.
The price taker tool engine formulates an optimal dispatch (co-optimization) to maximize the total benefits for given energy, ancillary services, and reserve as well as capacity market prices, considering tradeoffs among all the stacked value streams. Since a PSH plant can operate at different modes (e.g., generating, pumping, HSCs, and standing-by modes), the optimal dispatch problem involves several conditional expressions and nonlinear constraints and therefore is cumbersome to solve. To address these nonlinearities, binary decision variables are introduced, and the original nonlinear co-optimization problem is then transformed into an equivalent mixed-integer linear programming problem, which can be solved using off-the-shelf optimization solvers.
The price influencer tool embedded in the PSHVT is based on the A-LEAF model developed by Argonne National Laboratory. A-LEAF is an integrated national-scale power system simulation framework that includes a suite of capacity expansion, unit commitment, and economic dispatch models, as described in Figure 3. A-LEAF can determine the least-cost generation investment and retirement plan, transmission investment plan, and hourly or subhourly system scheduling, all under a range of user-defined input assumptions for technology characteristics, electricity demand profiles, and system requirements for electricity market designs.
The price influencer tool assesses various PSH use cases included in the PSHVT, based on the valuation process described in the Pumped Storage Hydropower Valuation Guidebook. The price influencer tool uses two main models in A-LEAF: the 1) long-term generation and transmission expansion planning (GTEP) model and 2) short-term system operational model.
First, the PSHVT performs long-term GTEP through the model, with and without the PSH plant of interest. This process determines how the presence of the PSH plant can influence the future generation portfolio and transmission topology by reducing the need for constructing additional generating or transmission capacity. The determined future generation portfolio and transmission topology will be used in the short-term system operation models to perform additional valuation analysis.
The GTEP model is a least-cost mixed-integer linear programming model that determines the time, location, and size of new generation and transmission assets in the system while ensuring that the total expected cost of the power supply, including investment and operating costs, is minimized. The least-cost objective function includes the costs of new generation investment and retirement, fixed and variable operation and maintenance (O&M), fuel, involuntary load curtailment, and applicable policy-related incentives or requirements. System costs are minimized while considering constraints related to regional generation investments, system operations, system resource adequacy, technical characteristics of generating and storage resources (including PSH), and policies and regulations.
Second, the PSHVT conducts production cost simulations using the security-constrained economic dispatch model in A-LEAF to determine the optimal scheduling of generation and energy storage assets, including PSH, as well as the procurement of required ancillary services. The production cost simulations are performed for a full year, utilizing the generation mix and transmission topology obtained from the long-term planning analysis. The formulation of the economic dispatch model involves several key constraints that help ensure the efficient and reliable operation of the power system. The load balance constraint ensures that the total demand for power in each region is met by the generation resources available during each time interval. The power flow and transmission limit constraints ensure that the power transmitted over the grid is within the safe limits of the transmission lines. The tool represents the U.S. power grid, using 134 balancing areas (BAs). The “pipe-and-bubble” network flow model is employed to capture the transfer capabilities among regions. Finally, the operating reserve requirements constraint procures operating reserves to meet system requirements while respecting the operating limits of generation and storage resources.
The tool considers a range of policies and regulations, including technology-specific investment tax credits, production tax credits, renewable portfolio standards (RPSs), limits on carbon emissions, and an internalized cost of carbon, through predesigned scenarios. Default policy settings are provided for each scenario, and users have the flexibility to adjust the policy parameters as required. The A-LEAF simulations utilize these policy parameters to capture the impact of the modeled policies and regulations.
As mentioned, the tool uses 134 BAs to represent the U.S. power grid, as detailed in Figure 4. Users may select the BA in which the PSH plant should be modeled by using this map, and that BA will serve as the focus of the valuation assessment.
A-LEAF includes a detailed representation of the physical and operational constraints of energy storage resources. The model allows energy storage resources to provide capacity, energy, and operating reserves. In addition, A-LEAF manages the state-of-charge (SOC) levels of energy storage resources, based on the chronological interactions of charging and discharging schedules. SOC management also involves maintaining sufficient headroom and energy reserves to provide ancillary services, as explained in Figure 5. Moreover, the storage capacity of chemical energy storage technologies degrades over time, based on how they are operated. In A-LEAF, the total amount of energy a storage resource can be expected to store and deliver over a year is considered by an energy throughput constraint. The energy throughput constraint is a proxy for capturing cycle life specifications of energy storage resources, particularly battery storage technologies.
The price influencer tool supports various PSH use cases included in the PSHVT from the perspectives of the power system and project owner, as summarized in Table 2. The output of the price influencer tool is provided to the PSHVT for synthesis in the BCA.
Table 2. The PSH use cases supported by the price influencer tool in the PSHVT.
The price influencer model is more appropriate for large-scale PSH plants because it accounts for the impacts of plant operations on regional power flows and prices. However, there is a variety of complexities that affect the ability of the approach to yield realistic results for future operations:
To demonstrate an application of the PSHVT, four cases (a base case, a 50% RPS, a US${\$}$40 carbon tax, and a high natural gas price of US${\$}$4.79/million British thermal units) were run for a hypothetical 100-MW/1-GWh PSH plant sited in three regions of the United States: BA P9, stretching from the Oregon/California border down along the coastline to Southern California, in the California Independent System Operator (CAISO) territory; BA P131, covering most of Massachusetts, including Boston, in the ISO New England (ISO-NE) market territory; and BA P122, covering most of Pennsylvania, in the PJM Interconnection territory.
The BCA model requires detailed information for several key financial parameters. These parameters, including the defined value and basis of each value are listed in Table 3. Key inputs include a project cost of US${\$}$263.5 million, US${\$}$2.8 million in annual fixed O&M costs, a five-year project development period, a 100-year BCA period, a 6.98% discount rate, and a 3% escalation rate for the value of services and capital/O&M costs. Note that all plant and financial assumptions, except capacity prices and corporate tax rates, are applied identically in all three regions.
Table 3. The PSH plant and financial assumptions.
The results of the cases run using the embedded price influencer model are presented in Tables 4 and 5. Table 4 gives the annual value of each service measured by the PSHVT, while Table 5 provides the net present value (NPV), internal rate of return (IRR), and benefit–cost ratio (BCR) for all cases. The evaluation is performed from an owner–operator perspective, and the tool evaluates the benefits associated with bulk power capacity, electricity price arbitrage, frequency regulation, the contingency reserve, the flexibility reserve, and black start service. The results vary substantially depending on the region in which the simulation is performed and the case being examined. The results are driven by capacity, arbitrage, and regulation reserve values, while the flexibility reserve and black start service consistently yield negligible values. The value of PSH in CAISO is the highest among the three regions, with annual revenue topping US${\$}$20 million and BCRs ranging from 1.77 to 1.97. IRRs in California reach as high as 18.6% in the base and 50% RPS cases. The higher potential revenue in the CAISO region can be attributed to two main factors. First, the region has higher capacity prices compared to other regions, which contributes to increased revenue potential. Second, the retirement of aging thermal resources and higher penetration of renewable energy resources in the region increases the demand for a regulation reserve provision from the PSH plant. These factors together lead to higher potential revenue in the CAISO region. All cases in the PJM and ISO-NE regions fall short of US${\$}$14 million, with the US${\$}$40 carbon tax case generating the highest values and BCRs in both regions, at or near 1.4.
Table 4. The annual revenue by service, region, and scenario, in U.S. dollars.
Table 5. The financial results by region and scenario.
MCDA is a decision support tool that enables diverse stakeholders to consider a variety of concurrent goals when deciding on energy policies, initiatives, and infrastructure investments. It enables the user to broaden the analytical perspective beyond traditional monetary metrics to include broader environmental, resilience, social equity, and other goals. It follows a four-step process, as defined in Figure 6. The PSHVT walks the user through all four steps in the MCDA process.
The MCDA model is designed to produce performance indices for each alternative selected for analysis. An investment generating a higher performance index is more desirable, even if its goals are designed around minimizing the metrics.
The first step is to delineate the valuation criteria established earlier in the PSH valuation process by specifying the
The metrics can be categorized into three broad groups: 1) monetary, 2) physical or numerical, and 3) qualitative. The model allows the user to select from several broad categories of metrics. The user can define up to 20 metrics to include in the MCDA evaluation and can select multiple metrics for a single objective.
The second step is to determine impacts and define measurement scales and boundaries. Subject matter experts can be surveyed to define measurement scales for each selected metric and specify the boundaries (i.e., upper and lower limits associated with the scale). Scales can be set up such that they seek to either minimize (e.g., cost) or maximize the reported value (e.g., energy jobs).
Various measurement scales can be used to define the type of information provided by numbers:
The third step determines the relative importance of objectives to decision makers. To determine the relative importance of each objective, individual stakeholders could be asked to express the relative importance of each objective on a scale of zero to 100. The MCDA tool embedded in the PSHVT then computes a performance index value that ranges from zero to 100 based on the weights of each metric and values assigned to them. The performance index can be used to judge the relative merit of each alternative and is reflective of the full weight of the priority placed on each objective defined for the MCDA.
The back-end BCA calculator is engaged in step 12 of the BCA process defined in Figure 2. It runs the user through a series of data requests. The model enables the user to define alternative scenarios (e.g., the baseline, varying natural gas prices, and varying load growth), evaluate many use cases, and consider alternative debt structures, alternative depreciation methods, tax implications, salvage values, capital and O&M costs, and refurbishment costs. The BCA model calculates several financial metrics: the BCR, discounted payback period, NPV, and IRR for each case.
In the 15th and final step, the PSHVT produces a report that documents key user inputs throughout all 15 steps, and it reports the results of the BCA, MCDA, and price taker or price influencer models. The report can be printed or downloaded as a pdf.
While this tool may be of interest to a variety of stakeholders, it is primarily intended to aid the industry in applying the valuation framework and performing the valuation process described in the Pumped Storage Hydropower Valuation Guidebook. This decision tree-based tool provides valuation guidance for PSH developers, plant owners or operators, and other stakeholders, such as regulators, policy makers, and consultants, to assess the value of existing or potential PSH plants and their services. It brings the Pumped Storage Hydropower Valuation Guidebook to life, stepping the user through the 15-step BCA process and embedding all the tools required to determine the value of potential projects from an owner/operator, system, or societal point of view while evaluating metrics that are monetary, quantitative, or qualitative in nature.
The PSHVT provides a significant benefit to the hydropower industry and its stakeholders. Developing a valuation tool that is specifically designed to capture all services and contributions that PSH provides to the power system represents a big step forward in understanding the full value this technology brings to the grid, thus removing one of the obstacles faced by the industry.
The DOE’s WPTO has made a series of investments to advance the state of the art in the assessment of the value of PSH plants and their role in and contributions to the power system. The program developed a comprehensive and transparent valuation guidance that allows for consistent valuation assessments and comparisons of PSH projects. A five-lab consortium, led by Argonne, tested the PSH valuation guidance by applying it to two selected PSH projects: the 400-MW closed-loop Banner Mountain PSH project being pursued by Absaroka Energy, near Casper, WY, USA, and the 1,200-MW adjustable-speed technology closed-loop project being developed by Copenhagen Infrastructure Partners and Rye Development near the Oregon/Washington border, in Goldendale, WA, USA. The PSHVT was designed to provide a tool to industry as part of an effort to transfer and disseminate PSH valuation guidance to the hydropower industry, PSH developers, and other stakeholders. The latest phase of the program includes the US$4.3 million HydroWIRES TA program, providing direct national lab support to project sponsors.
The PSHVT provides enormous flexibility to developers, regulators, and other stakeholders interested in exploring the benefits of PSH. It allows users to evaluate several use cases spanning bulk energy, ancillary service, transmission, reliability, and even BTM services. It allows the user to evaluate the impact of alternative debt structures, depreciation treatment, and tax positions, including the investment and production tax credits codified in the Inflation Reduction Act. It allows the user to evaluate benefits from an owner–operator, system, or societal perspective for PSH plants located in one of 134 BAs across the United States. The tool allows users to evaluate the impact of alternative clean energy policies, including RPSs and carbon taxes, on PSH value, and it allows the user to explore the impact of PSH deployment on generation fleet emissions and fuel consumption by type. It also allows the user to evaluate PSH value by using baseline and numerous alternative scenarios varied based on natural gas prices, environmental regulations, and load growth. Thus, the tool enables users to conduct fairly comprehensive assessments of the economic feasibility of PSH projects in a simple and timely manner.
The DOE has engaged Argonne and PNNL to conduct an outreach campaign, providing demos at industry conferences, webinars, and one-on-one tutorials upon request. Upgrades to the PSHVT are also being considered. The actual use of the tool, particularly when employed for the HydroWIRES TA program, will develop additional requirements for the PSHVT as users determine their additional needs for energy storage valuation. Not until users have evaluated actual projects will some of the tool upgrades required become apparent.
Some upgrades have already been implemented due to suggestions by tool reviewers. One request resulted in the development of a downloadable version of the tool so that users can take the tool offline. Offline use can help prevent the loss of proprietary information and afford a sense of privacy that may not be felt when private information is online, even though it is on a protected server. In addition, a downloadable tool could be useful in areas without high-speed Internet or when there are significant intermittency issues. Another request suggested that it would be useful to share cases with colleagues. The authors have also considered making the PSHVT an open source tool. These and other upgrades will be defined and explored in future years. We hope you will test the PSHVT, and we will use your feedback as a mechanism for continual improvement.
The research work conducted by Argonne National Laboratory, INL, National Renewable Energy Laboratory, Oak Ridge National Laboratory, and PNNL for this project was funded by the WPTO, under the Office of Energy Efficiency and Renewable Energy, DOE.
V. Koritarov et al., “Pumped storage hydropower valuation guidebook: A cost-benefit and decision analysis valuation framework,” U.S. Department of Energy, Water Power Technologies Office, Washington, DC, USA, Mar. 2021. [Online] . Available: https://www.energy.gov/eere/water/pumped-storage-hydropower-valuation-guidebook-cost-benefit-and-decision-analysis
V. Koritarov, Q. Ploussard, J. Kwon, and P. Balducci, “A review of technology innovations for pumped storage hydropower,” U.S. Department of Energy, Hydro Wires, Washington, DC, USA, 2022. [Online] . Available: https://publications.anl.gov/anlpubs/2022/05/175341.pdf
P. Balducci et al., “Technoeconomic studies for the Goldendale energy storage project: Valuation framework test case study,” U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy. Washington, DC, USA, Argonne Report Number ANL-22/30, 2022. [Online] . Available: https://publications.anl.gov/anlpubs/2022/09/175685.pdf
P. Balducci et al., “Technoeconomic studies for the banner mountain energy storage project: Valuation framework test case study,” U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy. Washington, DC, USA, Argonne Report Number ANL-22/88, 2022. [Online] . Available: https://publications.anl.gov/anlpubs/2022/10/178619.pdf
Patrick Balducci is with Argonne National Laboratory, West Linn, OR 97068 USA.
Mark Weimar is with Pacific Northwest National Laboratory, Richland, WA 99354 USA.
Xu Ma is with Pacific Northwest National Laboratory, Richland, WA 99354 USA.
Di Wu is with Pacific Northwest National Laboratory, Richland, WA 99354 USA.
Jonghwan Kwon is with Argonne National Laboratory, Lemont, IL 60439 USA.
Anna Schleifer is with National Renewable Energy Laboratory, Golden, CO 80401 USA.
Vladimir Koritarov is with Argonne National Laboratory, Lemont, IL 60439 USA.
Sang-il Yim is with Argonne National Laboratory, Lemont, IL 60439 USA.
Bruce Hamilton is with Argonne National Laboratory, Lemont, IL 60439 USA.
Digital Object Identifier 10.1109/MPE.2023.3308240
Date of current version: 19 October 2023
1540-7977/23©2023IEEE