Research on short-term photovoltaic power prediction method based on WOA-SVM

Inhalt:
To predict photovoltaic power generation more accurately, aiming at the problem of low prediction accuracy caused by improper parameter selection in the support vector machine model, a short-term photovoltaic output prediction model based on a whale optimization algorithm to optimize support vector machine parameters is proposed. Firstly, the whale optimization algorithm is used to optimize the parameters of the support vector machine. Secondly, the optimized algorithm model is used for photovoltaic power output prediction. Finally, the output power of photovoltaic power stations under three different weather conditions is predicted and simulated. The prediction results are compared with the prediction results of SVM, PSO-SVM, and ARIMA methods. The results show that the WOA-SVM algorithm can effectively improve the accuracy of short-term photovoltaic power prediction.