Energy Storage System Planning Based On Medium And Long Term Load Forecasting

With the massive exploitation and utilization of fossil energy by human beings,traditional energy sources are increasingly scarce,and they also cause serious pollution to the environment.Therefore,the installed capacity of new energy power generation has rapidly increased.However,large-scale wind power and photovoltaic grid connection will bring great adverse effects on the grid,and at the same time increase the peak load pressure of the grid.Since the energy storage system can both stabilize the fluctuation of wind power output and photovoltaic output,it can also perform peak shaving on the power system containing wind power and photovoltaic power generation.Therefore,a reasonable planning must be made for the energy storage system of the power system with wind-generated electricity.When planning energy storage for a power system containing wind power and photovoltaic power generation,it is first to carry out medium and long-term load forecasting.Due to the large number of distributed power sources now connected to the grid and the number of electric vehicles are rapidly increasing in recent years.Therefore,this paper comprehensively considers factors such as economy,population,distributed power supply and electric vehicles,and establishes a multivariable residual modified grey prediction model to predict the load in medium and long term.Through comparative analysis of examples,it is proved that the model has a good forecasting effect in medium and long-term load forecasting.Reconstruct the power output of new energy sources.This paper first analyzes seasonal load characteristics and daily load characteristics of the area based on historical load data of a region.Then according to the analysis of the operational data of wind farms and photovoltaic power stations in the region,their output characteristics are obtained.Finally,the Markov chain-Monte Carlo method is used to reconstruct the power output of new energy in medium and long-term scale.After further analysis,the effectiveness of the method is proved.This paper divides the energy storage plan of a power system containing wind power and photovoltaic power generation into two parts.One part of the plan is to plan the battery energy storage system(BESS),which is used to stabilize the powerflow in the fluctuation of wind power.By controlling the state of charge of the BESS,it is effective to reduce the phenomenon of overcharging and overdischarging of the battery.Then comprehensive analysis from the perspective of operating costs,we can obtain the optimal BESS capacity for stabilize fluctuations.The optimum energy storage system capacity takes into account the operating life of the battery and the economics of the energy storage system.The other part is the planning of the pumped-storage power station required for peak shaving.Taking the maximum net income of the power system as the goal,the optimal capacity allocation model of the pumped storage power station required for peaking the power system with wind-generated electricity is established.The optimization of the capacity of the pumped-storage power station and the optimization of the output power of the pumped-storage power station are optimized for this model.Finally,through load forecasting data of a certain area and wind power system output reconstruction curve combined with existing power grid operating data for specific modeling and analysis,the results of the optimal energy storage configuration for peaking the grid in 2025 are obtained.