4.7 Article

An Insurance Contract Design to Boost Storage Participation in the Electricity Market

Journal

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
Volume 12, Issue 1, Pages 543-552

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2020.3011052

Keywords

Contracts; Insurance; Production; Generators; Energy storage; Electricity supply industry; Uncertainty; Energy storage; renewable energy; electricity market; decision-making; contract design

Funding

  1. NSF [CNS-1739295]
  2. Sandia National Lab [PO 2079716]

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This study proposes an insurance contract to compensate energy storage systems for providing flexibility and incentivize higher renewable participation in the electricity mix. The contract encourages renewable producers to bid higher and provides an additional source of revenue for storage owners.
Energy storage technologies are key to improving grid flexibility in the presence of increasing amounts of intermittent renewable generation. We propose an insurance contract that suitably compensates energy storage systems for providing flexibility. Such a contract provides a wider range of market opportunities for these systems while also incentivizing higher renewable penetration in the grid. We consider a day-ahead market in which generators, including renewables and storage owners, bid to be scheduled for the next operating day. Due to production uncertainty, renewable generators may be unable to meet their day-ahead production schedule, and thus be subject to a penalty. As a hedge against these penalties, we propose an insurance contract between a renewable producer and a storage owner, in which the storage reserves some energy to be used in case of renewable shortfalls. We show that such a contract incentivizes the renewable player to bid higher, thus increasing renewable participation in the electricity mix. It also provides an extra source of revenue for storage owners that may not be profitable with a purely arbitrage-based strategy in the day-ahead market. We validate our analysis through two case studies.

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