Stochastic Flexibility Evaluation for Virtual Power Plants by Aggregating Distributed Energy Resources  

作　　者：Siyuan Wang Wenchuan Wu Qizhan Chen Junjie Yu Peng Wang 

机构地区：[1]Department of Electrical Engineering,Tsinghua University,Beijing 100084,China [2]Zhongshan Power Supply Bureau of the Guangdong Power Grid Corporation,Zhongshan 528400,China [3]Beijing Qingda Gaoke System Control Company,Beijing 102208,China [4]CSEE [5]IEEE

出　　处：《CSEE Journal of Power and Energy Systems》2024年第3期988-999,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 National Natural Science Foundation of China under Grant U2066601,51725703;Southern Power Grid Technical Project GDKJXM20185069(032000KK52180069).

摘　　要：To manage a large amount of flexible distributed energy resources(DERs)in the distribution networks,the virtual power plant(VPP)is introduced into the industry.The VPP can optimally dispatch these resources in a cluster manner and provide flexibility for the power system operation as a whole.Most existing studies formulate the equivalent power flexibility of the aggregating DERs as deterministic optimization models without considering their uncertainties.In this paper,we introduce the stochastic power flexibility range(PFR)and timecoupling flexibility(TCF)to describe the power flexibility of VPP.In this model,both operational constraints and the randomness of the DERs’output are incorporated,and a combined model and data-driven solution is proposed to obtain the stochastic PFR,TCF,and cost function of VPP.The aggregating model can be easily incorporated into the optimization model for the power system operator or market bidding,considering uncertainties.Finally,a numerical test is performed.The results show that the proposed model not only has higher computational efficiency than the scenario-based methods but also achieves more economic benefits.

关 键 词：Chance constrained optimization combined model and data-driven stochastic power flexibility virtual power plant 

分 类 号：TM73[电气工程—电力系统及自动化]