A combination method in photovoltaic power forecasting based on the correlation coefficient

Photovoltaic (PV) power forecasting is one of the effective ways to decrease the influence caused by large-scale PV power station connecting to the grid. Currently, there are various forecasting methods. However, single forecasting method tends to perform unsatisfactorily. In this paper, a combination method in PV power forecasting based on the correlation coefficient was proposed. Firstly, the persistence method, support vector machine (SVM) method and prediction method based on similar data were used to forecast the PV power separately. Then the weight of single prediction method was determined by the correlation coefficient of prediction and actual values. Single prediction method with larger correlation coefficient has greater weight. Finally, a combination model based on the correlation coefficient was established. By means of simulation and analysis, the combination prediction method based on the correlation coefficient was proved to be effective and the prediction accuracy was improved.