Research On Wind And Solar Complementary Charging Station Based On Particle Swarm Optimization

Electric vehicle will not pollute the environment by electric energy,and charging station is the main factor that restricts the development of electric vehicle.Building charging stations is just as important as developing electric vehicles.Distributed power sources in charging stations use renewable energy to generate electricity and clean energy to meet the need to alleviate the energy crisis and environmental pollution.All countries are beginning to attach importance to the construction of charging stations composed of various renewable energy sources.However,the wind and photovoltaic generators in the charging station system change with the change of meteorological conditions,and the weather conditions are changing at any time.So the drawback is that the output power is uncertain and volatile,which makes it more complicated when the charging station is transmitted,and the reliability of the charging station will be affected.It is more necessary to optimize and manage the energy in the charging station.In this paper,the complementary charging station of the scenery is taken as the research object.The problem of power optimization in independent and grid-connected mode is studied.Quantum genetic algorithm and particle swarm optimization(PSO)are used to solve the optimal scheduling of charging stations respectively.The principle of power generation,the characteristics of power generation and the environmental benefits are studied.The optimization model of charging station under independent operation and grid-connected operation is established.The following two objective functions are considered: the minimum comprehensive freight cost of charging station in independent operation mode.In the grid-connected operation mode,the total income of charging station is the largest,and the constraints are considered: power balance constraint,output power constraint of micro-power source and storage battery operation constraint,etc.A more comprehensive power optimization model of charging station is established,and the optimal scheduling strategy under different modes is given,and the corresponding optimization models in different modes are constructed respectively.There are many constraints for the power optimization model of charging station.Quantum genetic algorithm and PSO algorithm are used to solve the optimal model of charging station,and quantum genetic algorithm and PSO algorithm are used to solve the system of wind and wind complementary charging station.The simulation of the charging station in grid-connected and isolated island operation is carried out,the advantages and disadvantages of the two algorithms are compared,the main research results of this paper are summarized and the direction of the future work is clarified.