Forecast Of Wind And Photovoltaic Power Generation And Combined Operation Of Wind,Photovoltaic And Pumped-storage Power Stations

In the face of the growing shortage of fossil fuels and environmental pollution caused by them,wind energy and solar energy are undoubtedly the new energy sources occupying important positions.Wind power and photovoltaic power generation are the new energy generation technologies that have been developing more rapidly in recent years,but due to wind energy and solar energy natural uncertainties and intermittences make wind power and photovoltaic power generation affect the stability of the power grid when it is transmitted into the power grid.Pumped-storage power stations are used as energy storage devices for wind and photovoltaic power generation to effectively solve related problems.This paper will study the wind and photovoltaic power generation forecast and the combined operation system consisting of wind,photovoltaic and pumped-storage power stations.On the one hand,forecasting wind and photovoltaic power generation can reduce the impact of wind and photovoltaic power generation uncertainty on the grid to a certain extent and provides a basis for combined operation system consisting of wind,photovoltaic and pumped-storage power stations.On the other hand,the establishment of combined operation systems can,to some extent,reduce the impact of the intermittent and volatility of wind and photovoltaic power generation on the power grid.This paper first introduces a new proposed algorithm and its corresponding multiobjective algorithm,and tests its performance.Next,in order to reduce the impact on the grid for the uncertainty of wind and light power generation,this paper studies the forecast of wind and photovoltaic power generation.In the case that the related prediction methods have been developed,this paper has studied the improvement in performance of single prediction methods.The BP neural network based on wavelet analysis theory has been used to predict the wind power generation time series and adopt the support vector machine and BP neural network combination forecast method predicts the photovoltaic power generation power,and the main purpose is to add different ideas and technologies based on the original prediction method to improve the prediction effect.The prediction results show that the idea of adding wavelet analysis process and combined forecasting can improve the prediction results of wind and photovoltaic power generation to a certain extent.Then this paper elaborates the operating characteristics of pumped-storage power stations and their main role in the entire power production process,and establishes wind,photovoltaic,and pumped-storage power station combined operation system model that are optimized for multi objective of generation benefits and most smooth output power to the external power grid.The principle and their scheduling methods of combined operation system of wind,photovoltaic,and pumped-storage power stations were studied.Afterwards,based on the prediction data of wind and photovoltaic power generation and the established wind,photovoltaic,pumped-storage power station combined operation model,combined with an example,MSSA was used to solve the model for multi-objective optimization,supplemented by the concept of non-dominated solution membership and the corresponding penalty function-based constraint processing strategy to obtain the power sequence transmitted to the power grid by the combined operation system,and under the equal conditions,optimize the sole objective of generation benefits or the most smooth output power to the external grid,and compare the optimization results.The results show that pumped-storage power stations can realize the function of weakening the fluctuation of the wind and photovoltaic power generation in wind,photovoltaic,and pumped-storage power generation combined operation systems,maintain the stability of the entire system,and can increase the utilization rate of wind and photovoltaic energy and reduce the waste of energy to some extent.