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Grid Strategy 2011: Energy Storage Monetization—An Overview of the EPRI Energy Storage Valuation Tool V3.0 and Smart Grid Case Studies

Energy storage is the only grid asset with the ability to act both as a load and a generation source by first storing energy for a limited duration and then releasing it. It is a flexible grid asset capable of providing multiple grid benefits. However, aside from large pumped hydro storage plants, very little energy storage has been deployed on the grid. Due to the high cost of energy storage, aggregation of multiple benefits is generally required to justify the investment. Due to the limited duration of energy storage, a granular dispatch simulation is required to understand the economics of storage. To this end, EPRI has developed the Energy Storage Valuation Tool (ESVT) 3.0.

The ESVT is a user-friendly, transparent, and robust economic decision model that allows users to evaluate the costs and benefits of grid-connected energy storage systems. It is based on a third-party decision support software platform called Analytica™ developed by Lumina Systems. This report explains the user interface of the tool and its two modes of operation: Opportunity Scanning mode and Site-Specific Analysis mode.

This report also covers two ESVT case studies conducted by EPRI with utilities from the Smart Grid Demonstration Program. The purpose of these case studies was to identify key issues with the ESVT prototype software. The first case study investigated the value of a compressed air energy storage system (CAES) in a bulk, wholesale electricity market. The purpose of this system was to earn revenues by accruing the benefits of increased system capacity, energy arbitrage, and frequency regulation. The second case study investigated a distributed energy storage system proposed for the purpose of deferring a distribution investment, integrating distributed photovoltaics, and earning additional market benefits, where possible.

In the process of performing the case study, the EPRI team became aware of multiple issues with the ESVT model; and some of the improvements suggested by this research were incorporated in the ESVT system prior to the release of the prototype. The team made other recommendations for future research.

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