Capacity Optimization Of Off-grid Wind-solar Complementary EV Charging Station

In order to solve the problem of new energy given mass charging electric cars as the load connected to the electricity grid and cause the loss of the power grid stability problems,combining with the Inner Mongolia autonomous region provincial channel line is long,and the characteristics of network remote wind-light complementary system is proposed to combine with electric vehicle charging stations in composition from net scenery complementary type electric vehicle charging stations.In order to improve the economy of this type of charging station,this paper studies the optimal capacity allocation of off-grid wind-solar hybrid EV charging stations.The details are as follows:(1)The wind power generation and photovoltaic power generation output models are established based on the actual annual climate data of a certain region in Inner Mongolia,and the charging and discharging models of energy storage batteries are established on the basis of efficient and safe utilization of energy storage batteries.Finally,the charging load of electric vehicles is modeled based on the principle of energy equivalence,and the charging station load model is obtained.(2)Under the constraints of operating reliability,minimum power,floor area and installed capacity of charging stations,an optimization model of scenic storage capacity was established with the lowest cost of charging stations as the objective function.(3)In order to solve the shortcomings of the standard genetic algorithm,which is prone to local convergence and slow optimization speed,an improved two-population genetic algorithm is proposed in this paper to optimize the capacity configuration of wind turbines,photovoltaic cells and energy storage cells.An adaptive particle swarm optimization algorithm with excellent performance in convergence and optimization speed is selected as a comparison algorithm to prove the superiority of the proposed algorithm.(4)Based on the real-time data of annual wind speed,light intensity and temperature in a certain region of Inner Mongolia in 2018,adaptive particle swarm optimization algorithm,genetic algorithm and improved two-population genetic algorithm were respectively adopted to solve the optimal configuration problem of charging station capacity in MATLAB environment.The results show that the improved two-population genetic algorithm has more advantages than the other two algorithms in terms of optimization speed and cost saving.