首页|Energy Management of Price-maker Community Energy Storage by Stochastic Dynamic Programming

Energy Management of Price-maker Community Energy Storage by Stochastic Dynamic Programming

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In this paper,we propose an analytical stochastic dynamic programming(SDP)algorithm to address the optimal management problem of price-maker community energy storage.As a price-maker,energy storage smooths price differences,thus decreasing energy arbitrage value.However,this price-smoothing effect can result in significant external welfare changes by reduc-ing consumer costs and producer revenues,which is not negligible for the community with energy storage systems.As such,we formulate community storage management as an SDP that aims to maximize both energy arbitrage and community welfare.To incorporate market interaction into the SDP format,we propose a framework that derives partial but sufficient market information to approximate impact of storage operations on market prices.Then we present an analytical SDP algorithm that does not require state discretization.Apart from computational efficiency,another advantage of the analytical algorithm is to guide energy storage to charge/discharge by directly comparing its current marginal value with expected future marginal value.Case studies indicate community-owned energy storage that maximizes both arbitrage and welfare value gains more benefits than storage that maximizes only arbitrage.The proposed algorithm ensures optimality and largely reduces the computational complexity of the standard SDP.

Analytical stochastic dynamic programmingenergy managementenergy storageprice-makersocial welfare

Lirong Deng、Xuan Zhang、Tianshu Yang、Hongbin Sun、Yang Fu、Qinglai Guo、Shmuel S.Oren

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Department of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200000,China

Tsinghua-Berkeley Shenzhen Institute,Tsinghua University,Shenzhen 518055,China

Risk Analytics and Optimization Chair,EPFL,Switzerland

Power Systems Laboratory,ETH Zurich,8092 Zurich,Switzerland

State Key Laboratory of Power Systems,Department of Electrical Engineering,Tsinghua University,Beijing 100084,China

Department of Industrial Engineering and Operations Research,University of California Berkeley,Berkeley,CA,USA

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国家自然科学基金Shanghai Sailing ProgramState Key Laboratory of Power System Operation

U206621422YF1414500SKLD22KM19

2024

10.17775/CSEEJPES.2023.02720

中国电机工程学会电力与能源系统学报(英文版)
中国电机工程学会

中国电机工程学会电力与能源系统学报(英文版)

CSTPCDEI
ISSN：2096-0042
年,卷(期)：2024.10(2)
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