Electric vehicle optimal scheduling method considering charging piles matching based on edge intelligence  

作　　者：Ning Guo Tuo Ji Xiaolong Xiao Tiankui Sun Jinming Chen Xiaoxing Lu Xinyi Zheng Shufeng Dong 

机构地区：[1]Electric Power Research Institute,State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing 211100,China [2]College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China

出　　处：《iEnergy》2024年第3期152-161,共10页电力能源汇刊（英文）

基　　金：supported by the Science and Technology Project of State Grid Jiangsu Electric Power Company(J2023114).

摘　　要：To adress the problems of insufficient consideration of charging pile resource limitations,discrete-time scheduling methods that do not meet the actual demand and insufficient descriptions of peak-shaving response capability in current electric vehicle(EV)opti-mization scheduling,edge intelligence-oriented electric vehicle optimization scheduling and charging station peak-shaving response capability assessment methods are proposed on the basis of the consideration of electric vehicle and charging pile matching.First,an edge-intelligence-oriented electric vehicle regulation frame for charging stations is proposed.Second,continuous time variables are used to represent the available charging periods,establish the charging station controllable EV load model and the future available charging pile mathematical model,and establish the EV and charging pile matching matrix and constraints.Then,with the goal of maximizing the user charging demand and reducing the charging cost,the charging station EV optimal scheduling model is established,and the EV peak response capacity assessment model is further established by considering the EV load shifting constraints under different peak response capacities.Finally,a typical scenario of a real charging station is taken as an example for the analysis of optimal EV scheduling and peak shaving response capacity,and the proposed method is compared with the traditional method to verify the effectiveness and practicality of the proposed method.

关 键 词：Edge intelligence electric vehicle charging pile optimal scheduling matching relationship peak shaving responsiveness 

分 类 号：TU4[建筑科学—土工工程]