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

作　　者：Lirong Deng Xuan Zhang Tianshu Yang Hongbin Sun Yang Fu Qinglai Guo Shmuel S.Oren 

机构地区：[1]Department of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200000,China [2]Tsinghua-Berkeley Shenzhen Institute,Tsinghua University,Shenzhen 518055,China [3]Department of Industrial Engineering and Operations Research,University of California Berkeley,Berkeley,CA,USA [4]Risk Analytics and Optimization Chair,EPFL,Switzerland,and also with Power Systems Laboratory,ETH Zurich,8092 Zurich,Switzerland [5]State Key Laboratory of Power Systems,Department of Electrical Engineering,Tsinghua University,Beijing 100084,China

出　　处：《CSEE Journal of Power and Energy Systems》2024年第2期492-503,共12页中国电机工程学会电力与能源系统学报（英文）

基　　金：supported in part by the Joint Funds of the National Natural Science Foundation of China(U2066214);in part by Shanghai Sailing Program(22YF1414500);in part by the Project(SKLD22KM19)funded by State Key Laboratory of Power System Operation and Control.

摘　　要：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.Index Terms-Analytical stochastic dynamic programming,energy management,energy storage,price-maker,social welfare.

关 键 词：Analytical stochastic dynamic programming energy management energy storage price-maker social welfare 

分 类 号：TM73[电气工程—电力系统及自动化]