Considering the objective needs of the grid side and user side in the current charging process of electric vehicles,a method for optimizing the orderly charging of electric vehicles has been designed.A time dimension scheduling model for electric vehicles is established with the objective function of minimizing load fluctuations on the grid side and maximizing the charging capacity of electric vehicles on the user side.An improved multi-objectiveparticle swarm optimization algorithm is proposed to speed up the search efficiency and jump out of the local extremum through individual selection,normal distribution adaptive mutation,fuzzy satisfaction decision and other strategies.The experiment results indicate that IACO has higher search efficiency compared to MOGA and MOAFSA.
Key words
power system /
electric vehicles /
charging strategy /
ant colony optimization
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