doi:10.16186/j.cnki.1673-9787.2021020017

Received:2021/02/04

Revised:2021/03/24

Published:2022/03/15

Multi-scene distributed generation planning based on clustering by fast search and find of density peak

WU Xiaomeng1, SHI Zheng1, FU Ziyi2, LIU Xinyu3, DANG Jian1, LI Fei1

1.Key Laboratory of Measurement and Control Technique of OH and Gas Well of Shaanxi Province, Xi ’ an Shiyou University, Xi ’ an  710065 , Shaanxi, China;2.School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo  454000 , Henan, China;3.Dalian Branch , China National Petroleum Corporation Research Institute of Safety & Environment Technology, Dalian  116031 , Liaoning, China

Abstract: Aiming at the problems of the randomness of intermittent distributed generation output,the uncertainty of load demand,and the correlation between distributed generation and load,Latin hypercube sampling and Cholesky decomposition combined with Spearman rank correlation coefficient were used to obtain an output and demand load relevant sample of distributed generation.The relevant sample was reduced by the algorithm of clustering by fast search and find of density peak(CFSFDP) to obtain typical scenes.The multi-objective distributed generation planning model was established with the optimization goal to minimize the investment and operation cost of the distributed generation and the power purchase cost of the superior grid.The programming model was transformed into a mixed-integer second-order cone programming( SOCP) problem through secondorder cone relaxation,and the Cplex solver was called to solve the programming model.The results of IEEE 33-bus distribution network were applied to verify the rationality of the proposed model and method.

Key words:distributed generation planning model;Spearman rank correlation coefficient;clustering by fast search and find of density peak;second-order cone programming

基于密度峰值快速搜索聚类的多场景分布式电源规划_武晓朦.pdf