A source-network-storage collaborative planning method for distribution networks based on random scenarios
DOI:10.19783/j.cnki.pspc.240745
Key Words:distribution network  source-network-storage collaborative planning  Copula theory  random scenarios  mixed integer second-order cone programming
Author NameAffiliation
LE Jian1 1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
2. School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
3. Wuhan YICIYUAN Power Technology Co., Ltd., Wuhan 430223, China 
WANG Jing1 1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
2. School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
3. Wuhan YICIYUAN Power Technology Co., Ltd., Wuhan 430223, China 
LIAO Xiaobing2 1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
2. School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
3. Wuhan YICIYUAN Power Technology Co., Ltd., Wuhan 430223, China 
WANG Weihao1 1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
2. School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
3. Wuhan YICIYUAN Power Technology Co., Ltd., Wuhan 430223, China 
MAO Tao3 1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
2. School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China
3. Wuhan YICIYUAN Power Technology Co., Ltd., Wuhan 430223, China 
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Abstract:To deal with the uncertainty of PV output and load demand in the source-network-storage collaborative planning method for distribution networks, a source-network-storage collaborative planning method for distribution networks based on random scenarios is proposed. First, a source-load correlation probability model is established based on the Copula theory, and scene generation and reduction is carried out by the Monte Carlo method and K-means clustering algorithm, so as to obtain the source-load correlation output curve of a typical daily scene. On this basis, to improve the efficient consumption of PV and the planning economy of distribution networks, studies on the source- network-storage collaborative planning for distribution networks based on random scenarios are carried out, and the joint planning model of PV, energy storage system (ESS) and grid expansion is established. Finally, through the simulation analysis of 25-bus and 54-bus systems in a certain area, it is verified that the proposed method can effectively mitigate the impact of PV and load uncertainties on the distribution networks, and significantly improve the PV absorption capacity as well as the overall economy of distribution network planning.
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