Power Prediction of Photovoltaic Power Generation Based on OOA Optimised BP Neural Network
Accurate prediction of photovoltaic(PV)power generation is a key link to ensure the smooth operation of the power grid,but due to the large number of input variables of the PV power generation system,the accuracy of the standard BP neural network system for power generation prediction is not ideal.The prediction model based on OOA optimised BP neural network(OOA-BP)can improve the prediction accuracy.Six types of data,namely,total irradiance,direct radiation,scattered radiation,air temperature,barometric pressure,and humidity,were used as inputs to the OOA-BP neural network prediction model and their prediction results were compared with the standard BP neural network.The results show that compared with the standard BP neural network model,the OOA-BP neural network prediction model can effectively improve the prediction accuracy and prediction eficiency of photovoltaic power generation by optimising the thresholds and weights.
OOA optimisation algorithmBP neural networkphotovoltaic power prediction
NETL
NSTL
万方数据
