Electric Vehicle Charging Station Planning Based on Multiple-Population Hybrid Genetic Algorithm

Establishing electric vehicle charging station´s minimum comprehensive cost model which considers charging station´ construction and operation cost and the cost of charging people. According to the characteristics of the electric vehicle charging station planning, this article puts forward a new kind of Multiple-Population Hybrid Genetic Algorithm (MPHGA). The algorithm combines the Standard Genetic Algorithm (SGA) with Alternative Location and Allocation Algorithm (ALA). According to the multi-objective of the charging station planning, use the concept of multigroup to do collaborative evolution search. Based on the Geographic Information System (GIS), the geographic information´ influence on the location of the charging station will be considered. The model and method are proved that they have great correctness and effectiveness by a charging station planning example of a city.