Research On Optimization Of Photovoltaic Energy Storage System Based On Genetic Algorithm

Distributed photovoltaic power generation is gradually becoming the mainstream power generation mode with the gradual depletion of fossil energy.At present,the improvement of photovoltaic benchmarking electricity price and the formulation of compensation price rules in China indicate that our country is paying more and more attention to distributed power generation year by year.Among many new energy generation methods,photovoltaic power generation is becoming the main force instead of traditional power generation because of its wide distribution of raw materials and no carbon emission in the process of power production.However,due to the limitations of photovoltaic power generation principle,energy storage system must be equipped to solve the problem of photovoltaic power generation output stability.Because the energy storage system plays an important role in the photovoltaic power generation system,and it is of great benefit to realize the peak cutting and valley filling of the power grid load,it is of great significance to study the optimization method of the photovoltaic power generation energy storage system.For this reason,this paper mainly carries on the following several aspects the research:Firstly,the working characteristics and mathematical model of the basic components of the energy storage system are briefly introduced,and the aging mechanism of the battery and the life model of the battery are analyzed.On this basis,the cost calculation function of photovoltaic power station considering battery loss is put forward.At the same time,based on the concept of low carbon emissions from new energy power generation,the carbon emissions in the life cycle of photovoltaic power stations are analyzed.Then under the peak and valley electricity price policy,the economical function of photovoltaic power station is put forward.Finally,a multi-objective programming problem with charging start and end time and energy storage capacity as independent variables is formed.Secondly,the non-dominant sorting genetic algorithm with elite strategy(NSGA-?)is introduced.After comparing it with the basic genetic algorithm,it is concluded that the NSGA-? is superior in multi-objective optimization.Then the implementation method of its application in the optimization problem of energy storage system is analyzed.Taking 1MW photovoltaic power station of Shenyang Tianrun Thermal heating Company as an example,the multi-objective programming problem of energy storage system based on undominated sequencing genetic algorithm with elite strategy is solved.Finally,in order to solve the problem that it is difficult to select the optimal solution of Pareto in engineering,the method of membership degree and variance weighting is introduced,and the optimal solution is selected.Finally,taking 1MW photovoltaic power station of Shenyang Tianrun Thermal heating Company as an foundation,the multi-objective programming problem of energy storage system based on NSGA-? is solved.The optimization scheme of photovoltaic energy storage system based on peak and valley price is obtained.Finally,the return on investment cycle of photovoltaic power station without energy storage is compared with that of photovoltaic power station in this example,it is concluded that the economy,carbon emission and construction cost of photovoltaic power generation system are the best.