A Hybrid Intelligent System Approach to Forecasting of PV Generation Output

다국어 초록 (Multilingual Abstract)

In this paper, a hybrid intelligent method is proposed to deal with the prediction of PV generation output. It is important to predict PV generation output with high accuracy and smooth operational planning. The proposed method integrates Generalized Radial Basis Function Network (GRBFN) of Artificial Neural Network (ANN) with Deterministic Annealing (DA) clustering of globally optimal clustering to improve the performance of the conventional Radial Basis Function Network (RBFN). The use of DA is effective for determining better initial values of the GRBFN parameters. In practice, GRBFN outperforms RBFN in a way that the parameters of the radial basis function are determined by the learning process. The effectiveness of the proposed method is demonstrated in real data.