Multi-objective EV Charging Task Sequence Optimization Model Based on GRASP-PR Hybrid Algorithm
This paper proposes a multi-objective EV charging task sequence optimization model based on GRASP-PR hybrid al-gorithm to improve the peak shaving and valley filling capacity of the distribution network and ensure its stable operation.Based on the characteristics of EV travel and the analysis of the impact of disordered charging mode on the peak-valley differ-ence of distribution network load,an EV charging task sequence optimization model is constructed.The greedy randomized adaptive search algorithm that introduces path relinking strategy is used to solve the optimization model and determine the opti-mal EV charging task sequence scheduling scheme.The experimental results show that under the disordered charging mode,the more EVs are connected to the grid for charging,the greater the peak-valley difference of the distribution network load.This optimization model can achieve the optimization control of EV charging task sequence,achieve the effect of peak shaving and valley filling,and reduce the operating cost of the distribution network and EV charging cost.
GRASP-PR hybrid algorithmEV charging task sequenceoptimization modelpeak shaving and valley fillingdis-ordered sequence charging mode
万方数据
维普
