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Open Access

An Efficient Decomposition Method for Bilevel Energy Storage Arbitrage Problem

Danman WuTengyun QiWei Wei ( )Jianping LiuLaijun ChenShengwei Mei
State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
China Three Gorges Corporation, Beijing 100038, China
China Three Gorges Renewables (Group) Co., Ltd., Beijing 100053, China
New Energy Industry Research Center, Qinghai University, Xining 810016, China
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Abstract

With the reduction of cost, large-capacity energy storage unit is playing an increasingly important role in modern power systems. When a merchant energy storage unit participates in the power market, its arbitrage problem can be modeled via a bilevel program. The lower-level problem simulates power market clearing and gives the nodal price, based on which the upper-level problem maximizes the arbitrage profit of energy storage. To solve this bilevel problem, the conventional method replaces the lower level problem with its KKT optimality conditions and further performs linearization. However, because the size of the market clearing problem grows with the scale of the power system and the number of periods, the resulting MILP (mixed-integer linear program) is very challenging to solve. This paper proposes a decomposition method to address the bilevel energy storage arbitrage problem. First, the locational marginal price at the storage connection node is expressed as a piecewise constant function in the storage bidding strategy, so the market clearing problem can be omitted. Then, the storage bidding problem is formulated as a mixed-integer linear program, which contains only a few binary variables. Numeric experiments validate the proposed method is exact and highly efficient.

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CSEE Journal of Power and Energy Systems
Pages 652-658
Cite this article:
Wu D, Qi T, Wei W, et al. An Efficient Decomposition Method for Bilevel Energy Storage Arbitrage Problem. CSEE Journal of Power and Energy Systems, 2022, 8(2): 652-658. https://doi.org/10.17775/CSEEJPES.2021.02790

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Received: 10 April 2021
Revised: 21 May 2021
Accepted: 18 June 2021
Published: 05 January 2022
© 2021 CSEE
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