Capacity Ratio Method Of Electric Vehicle Charging Station With Scenery Storage

With the rapid development of the life scenery storage and electric vehicle charging is becoming more and more serious. This will stand with the scenery storage and electric vehicles off grid charging. According to the demand of electric vehicle charging, wind and solar power output data, as well as the operation cost to charge station economic benefit maximization as the goal, computing containing scenery storage of electric vehicle charging station of wind turbines, photovoltaic power generation unit, storage to battery capacity ratio, to meet regional electric vehicle charging requirements based on reduced with scenery storage of electric vehicle charging station cost and improve the rationality of the site planning.The from the following several aspects of scenery storage from the network type of electric vehicle charging station capacity ratio were studied: first of all, based on the statistics of electric vehicle charging power demand model of regional electric vehicle charging power demand. In charging equipment, charging with constant power under the premise, through to electric cars start charging time, long random process analysis of electric vehicle average 24 hours a day, every moment of charging power demand. Second, the calculation of the wind turbines, photovoltaic unit output, according to wind up to a year in average 24 hours a day, every hour, light, temperature data resources, scenery output equipment, scenery output model calculated average year 24 hours a day every hour of wind turbines, photovoltaic equipment output curve. The use of electric vehicle charging power demand, scenery storage capacity and power generation equipment such as number of constraints, the establishment of charging station to maximize the income of capacity ratio objective function model based on electric vehicle charging. The capacity ratio of the model was solved by scenery storage of electric vehicle charging station capacity ratio optimal results by improved genetic algorithm.At last, this paper chooses a highway intersection in Gansu as the research object of the electric vehicle charging station of the electric vehicle with wind scene. On average a day 600 electric car charging demand as load, and according to the local average day scenery resource data, respectively, with improved genetic algorithm and traditional genetic algorithm of scenery storage from the network type of electric vehicle charging station capacity ratio of research. Compared with the traditional algorithm, the improved genetic algorithm and the traditional algorithm are compared with the results of the improved genetic algorithm and the traditional algorithm. The simulation results show that the improved genetic algorithm can get more economic benefits than the traditional genetic algorithm.