Reactive Power Optimization Model of Active Distribution Network with New Energy and Electric Vehicles  

作　　者：Chenxu Wang Jing Bian Rui Yuan 

机构地区：[1]Northeast Electric Power University,Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology,Ministry of Education,Jilin,132011,China

出　　处：《Energy Engineering》2025年第3期985-1003,共19页能源工程(英文)

基　　金：funded by the“Research and Application Project of Collaborative Optimization Control Technology for Distribution Station Area for High Proportion Distributed PV Consumption(4000-202318079A-1-1-ZN)”of the Headquarters of the State Grid Corporation.

摘　　要：Considering the uncertainty of grid connection of electric vehicle charging stations and the uncertainty of new energy and residential electricity load,a spatio-temporal decoupling strategy of dynamic reactive power optimization based on clustering-local relaxation-correction is proposed.Firstly,the k-medoids clustering algorithm is used to divide the reduced power scene into periods.Then,the discrete variables and continuous variables are optimized in the same period of time.Finally,the number of input groups of parallel capacitor banks(CB)in multiple periods is fixed,and then the secondary static reactive power optimization correction is carried out by using the continuous reactive power output device based on the static reactive power compensation device(SVC),the new energy grid-connected inverter,and the electric vehicle charging station.According to the characteristics of the model,a hybrid optimization algorithm with a cross-feedback mechanism is used to solve different types of variables,and an improved artificial hummingbird algorithm based on tent chaotic mapping and adaptive mutation is proposed to improve the solution efficiency.The simulation results show that the proposed decoupling strategy can obtain satisfactory optimization resultswhile strictly guaranteeing the dynamic constraints of discrete variables,and the hybrid algorithm can effectively solve the mixed integer nonlinear optimization problem.

关 键 词：Active distribution network new energy electric vehicles dynamic reactive power optimization kmedoids clustering hybrid optimization algorithm 

分 类 号：TM714[电气工程—电力系统及自动化]