Research On Power Prediction Method Of Photovoltaic Power Generation System

Today’s world consumes huge amounts of energy,and countries all over the world attach great importance to the development and utilization of new energy sources.As a clean and renewable energy source,solar energy has huge potential.However,photovoltaic power generation is affected by meteorological factors such as radiation intensity and ambient temperature,resulting in a high degree of intermittency and volatility in the process of photovoltaic power generation.In order to reduce the phenomenon of abandonment of photovoltaic power plants,it is necessary to predict the photovoltaic power generation for power generation planning and energy-saving scheduling.This article first introduces the current domestic and foreign research on photovoltaic power generation power prediction,analyzes the correlation between photovoltaic power generation power and meteorological influencing factors,and determines the radiation intensity and ambient temperature as the main influencing factors affecting photovoltaic power generation.Then the similar daily power generation sequence,daily maximum irradiance intensity,daily average irradiance intensity,daily maximum,low temperature,and predicted daily maximum,low temperature,daily maximum irradiance intensity and daily average irradiance intensity are used as inputs,Finally,combining the empirical formula and trial and error simulation,the number of hidden layer nodes is determined,and the BP prediction model is established.Aiming at the shortcomings of the BP prediction model,a Swarm Intelligence Algorithm is proposed,and the Sparrow Search Algorithm is used to optimize the BP prediction model.The Sparrow Search Algorithm is compared with the Salp Swarm Algorithm and Ant Colony Optimization for performance testing.Aiming at the problem that the Sparrow Search Algorithm has the optimization effect and reduced stability in the multi-peak test function compared with the single-peak test function,the Levy flight improved Sparrow Search Algorithm is proposed to solve the shortcomings of the Sparrow Search Algorithm,and the improved Sparrow Search Algorithm is used to optimize the BP The model predicts photovoltaic power generation.In order to further verify the optimized BP model of Levy’s Sparrow,we compared it with the optimized BP model of Sparrow Search Algorithm,Salp Swarm Algorithm and Ant Colony Optimization.The experimental results show that the improved Sparrow Search Algorithm optimizes the BP model to further improve the prediction accuracy.