Photovoltaic Power Prediction Based on EEMD-SVR Model
Due to weather factors,photovoltaic output has strong uncertainty and volatility,making it difficult to predict photovoltaic power.A prediction method based on ensemble empirical mode decomposition(EEMD)and support vector regression(SVR)models is proposed for the prediction of photovoltaic power.Firstly,the photovoltaic power is decomposed into multiple characteristic mode components and a residual component through ensemble empirical mode decomposition.Secondly,use SVR model to train data and achieve component prediction.Finally,predict the photovoltaic power by combining the predicted components.The results indicate that the model can achieve reliable decomposition of non-stationary sequences and effectively improve the average absolute percentage error(MAPE)performance of photovoltaic prediction.
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