Research On Layout And Location Optimization Of Fast Charging Facilities For Urban Pure Electric Vehicles

As an important measure to alleviate the pressure of the petroleum resources dificiency and control air pollution, the development of electric vehicle have already received the vigorously sustain from all levels of the governments. Besides the maturity of the electric vehicle technology, the improvement of the infrastructure construction is also an important driving force for the development of electric vehicles, which means that one of the most important issues to be addressed is the layout and location of charging facilities.In order to get the scientific location scheme and enhance user convenience, this paper built up a layout and location optimization model of rapid charging facilities based on a variety of influencing factors, including user demands, investment costs, land location, emergency mileage limit, actual road condition and service network reliability. Then the paper proposed a solution procedure based on the improved genetic algorithm, and verified the feasibility of the model and the algorithm in case study.The specific contents are given as follows:(1) The factors influencing layout and location of the rapid charging facilities were analysed in details in this papaer. The factors mainly included user requirements, economic factors, traffic factors, power grid factors and service network reliability. Then measure methods about each factor during modeling were also analyesed in detail.(2) A multi-targent optimization model for layout location of fast charging facilities was built in this paper. The two targets were less investment costs and less user charging costs. On the basis of satisfying the user’s charging demands and the capacity constraints of charging stations, the model added the redundant design of charging spots and charging station, ensuring the reliability of the service network. The time factor and the distance factor were both considered in the allocation of charging requirements, which taking the time as the main consideration under the limit of emergency charging mileage. Besides, considerding the varying degrees of traffic congestion in different sections, an accounting method based on the land level is proposed in the calculation of the average speed of the road sections.(3) A solution procedure based on the improved genetic algorithm was proposed in this paper. The constraint conditions were processed by the combination of the refusal strategy and improved genetic operator strategy. The objective functions were normalized by the linear weighted method. Finally, a solution procedure was propsed based on the idea of enumeration method and genetic algorithm.(4) The model and the algorithm were verified through an actual case in this paper. Based on the relevant data of Linyi City, which was choosed as the actural case, the maximum evolutionary algebra and population quantity of genetic algorithm were calibrated by experiments. The model was solved by MATLAB software programming, which verified the effectiveness of the model and algorithm.(5) The extended research of the model was realized in this paper. In order to extend the applicable range of the model, the optimizations of the layout and location under different conditions were realized by simply adjusting the structure of the model. At the same time, the paper verified the feasibility of the adjusted models by solution calculation under the precondition of a given site number to.