Prediction method of distributed photovoltaic carrying capacity based on forward neural network
Photovoltaic energy is relatively scattered,and there are certain restrictions on the available capacity,which will affect the stability of the power system in the process of grid connection.A distributed photovoltaic carrying capacity based on forward neural network is proposed.Research on forecasting methods.Build a distributed photovoltaic power generation system model,in-depth a-nalysis of the influencing factors of distributed photovoltaic carrying capacity,with the goal of stable operation of the power system,construct a distributed photovoltaic carrying capacity prediction model,and determine the corresponding constraints,introduce and train a forward neural network,The data related to distributed photovoltaic grid connection is input into the trained forward neural net-work,and the output result is the prediction result of distributed photovoltaic carrying capacity.The experimental results show that the photovoltaic carrying capacity prediction time obtained by the proposed method is less than the given maximum limit,and the photo-voltaic carrying capacity prediction results are almost consistent with the actual results,which fully confirms the good application per-formance of the proposed method.
万方数据
维普
