Micro-grid Load Prediction And Research On Operation Control Method

As the country vigorously advocates the use of clean energy,the use of photovoltaic distributed generation microgrid systems has become an important trend in the field of power systems.However,the existing microgrid system has caused a lot of waste of resources due to lack of reasonable operation and control,which seriously restricts the development of clean energy.In order to maximize the economic benefits of the microgrid,this paper investigates the optimal control strategy for microgrids.In order to control the operation of the microgrid,it is necessary to predict the output of photovoltaic power generation and the user load power.For the output prediction of photovoltaic power generation,this paper uses K-S test to analyze the historical output data of photovoltaic power generation,and obtains the output characteristics,probability distribution function and characteristic parameter range under different meteorological conditions.The algorithm clusters generalized weather types into three groups.According to different clustering groups,the corresponding photovoltaic power generation prediction model was established based on the artificial neural network algorithm and verified by simulation.The results show that PV power prediction has good prediction accuracy under good meteorological conditions,and there is a certain deviation in the prediction accuracy for severe weather such as snow and wind.In order to realize the power forecast of user load,this paper studies the pattern recognition algorithm of support vector machine.The load forecasting model based on support vector machine is established and verified by simulation.The prediction accuracy of the model is high and the error is small.The model can meet the forecast demand of the typical user load.In order to maximize the economic benefits of the microgrid,this paper proposes a microgrid optimization control strategy based on multi-objective optimization function and artificial bee colony algorithm,which reduces the total operating cost of the microgrid and can significantly improve the microgrid while protecting the environment.economic benefits.