Abstract
Recently, the electric vehicles (EV) are promoting rapidly in many big cities of China, but the charging problem has become a big obstacle for the development of EV. In this article, the demand of EV is determined on the basis of EV proportion and divided into 2 portions: (1) Centralized demand (2) Decentralized demand. The charging total mileage is determined based on the state of charge (SOC) and the orderly-free charging strategy is presented considering the demand of the users. Moreover, a new multi-objective teaching–learning based optimization (MOTLBO) algorithm is put forward to plan the quantity and location of the concentrated charging pile in the region considering the situation of the new city. Results showed that the performance of MOTLBO was promising and benefits can be achieved easily. As Compared to other methods, the method used in this article picks out the hierarchical planning idea firstly and addicts the man–machine interaction into the free-orderly charging strategy.
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