Research On Energy Management Strategy Of Wind-solar Storage Microgrid

In recent years,as China’s low-carbon economy continues to deepen,clean and renewable energy power generation has also developed rapidly.Among them,the development of wind power and photovoltaic power generation is relatively rapid,and their installed capacity and power generation are increasing day by day.However,wind power and photovoltaic power generation also have significant shortcomings such as poor stability and strong volatility,which makes the grid connection of renewable energy power generation have some problems,such as waste of resources such as abandoning wind and solar.Lithium battery energy storage is the most commonly used energy storage method,which can make up for this shortcoming.This paper studies the energy management strategy of the wind and solar storage microgrid system.First,models of wind turbines,photovoltaic power stations,and lithium-ion battery energy storage devices are established,and then the BP neural network algorithm optimized by the improved wolf pack algorithm is used to predict wind power generation And the power of photovoltaic power generation,and finally set up a model of energy management strategy for wind and solar storage microgrid with the goal of optimal system operating cost and economy.First,the principles and mathematical models of wind turbines,photovoltaic power stations,and lithium-ion battery energy storage devices of the micro-grid system are introduced to provide a theoretical basis for subsequent research.Subsequently,the principles and shortcomings of the BP neural network algorithm and the wolf pack algorithm are introduced.Because these two algorithms have defects,the wolf pack algorithm is improved,and the improved wolf pack algorithm is optimized for the BP neural network algorithm for wind power generation.Power prediction for photovoltaic power generation.Analyzing the calculation example,comparing the prediction accuracy of traditional BPNN and optimized BPNN,it is obvious that the optimized BP neural network algorithm predicts the wind power power more accurately.Finally,the optimization goal is to lower the operating economic cost of the wind and solar storage microgrid system,and fully consider the real-time electricity price and environmental cost of the power exchange between the microgrid system and the main grid,as well as the wind turbines,photovoltaic generators and Cost of energy storage battery device,an energy management strategy model for the microgrid was established to optimize the microgrid system Scheduling.Finally,through the analysis of a calculation example,using particle swarm algorithm in MATLAB software to simulate and solve the operating cost of the microgrid system under the energy management strategy,and compare it with the economic cost under the conventional strategy.The operation of the microgrid system has higher economic efficiency.