Optimization of Charging/Battery-Swap Station Location of Electric Vehicles with an Improved Genetic Algorithm-Based Model

The joint location planning of charging/battery-swap facilities for electric vehicles is a complex problem.Considering the differences between these two modes of power replenishment,we constructed a joint location-planning model to minimize construction and operation costs,user costs,and user satisfaction-related penalty costs.We designed an improved genetic algorithm that changes the crossover rate using the fitness value,memorizes,and transfers excellent genes.In addition,the present model addresses the problem of“premature convergence”in conventional genetic algorithms.A simulated example revealed that our proposed model could provide a basis for optimized location planning of charging/battery-swapping facilities at different levels under different charging modes with an improved computing efficiency.The example also proved that meeting more demand for power supply of electric vehicles does not necessarily mean increasing the sites of charging/battery-swap stations.Instead,optimizing the level and location planning of charging/battery-swap stations can maximize the investment profit.The proposed model can provide a reference for the government and enterprises to better plan the location of charging/battery-swap facilities.Hence,it is of both theoretical and practical value.

Opportunity Cost Model of Infrastructure Access Charges for Chinese Railways

For the suppliers of concerned services, theories about infrastructure pricing： SAT （Stand Alone economists such as Laffont, Tirole, etc. developed Test）, ECPR （Efficient Component Pricing Rule）. Especially, Sidak, Spulber, put forward M-ECPR （Market Efficient Component Pricing Rule） method for bottleneck infrastructures. In this article, we bring the M-ECPR principles into the study of Chinese railways pricing of its network infrastructures. Combined with our Engineer Model and Opportunity Cost Model, we analyzed the special conditions faced by Chinese railways, and developed a model for sharing infrastructure fees among freight and passenger transportations. Engineer Model split Variable Cost （VC） and Fixed Cost （FC） into freight and passenger activities, and Opportunity Cost Model take the insufficient supply of infrastructure capacity into consideration. Of course, the subsidy from the government greatly affected the price standard for bottleneck facilities, or so-called network infrastructures.

Planning of electric vehicle charging infrastructure under the Background of Big Data

Today, the problems of power consumption and environmental pollution caused by road trafficare very serious. Automobiles produce large amounts of carbon monoxide and nitrogen, dust,and particles, which are the primary user of the fuel. Unconventional design methods will preventthe international process of replacing fuel-filled vehicles with electric vehicles. The promotionand adoption of electric vehicles can effectively alleviate these problems, but the planning ofelectric vehicle charging facilities needs to be resolved as soon as possible. The state-of-the-artmodeand power model of public charging equipment proposed in this paper can solve the problemof positioning charging equipment in large-scale transmission networks and research onrelated charging materials and location planning and energy model design methods that arebeneficial to the future development.