Abstract

Solar power is a giant natural reactor that provides far more energy that the human needs. In recent years, there are many photovoltaic (PV) types of equipment installing in on-grid and off-grid systems. This paper proposed an enhanced grey theory system model with weight table for PV power output forecast. Actual measured PV power generation data had implemented the proposed scheme and the other original schemes including back propagation neural network (BPNN) model, radial basis function neural network (RBFNN) model, and classical grey theory system model. Results of studied case are based on the proposed scheme to compare with another original schemes. It demonstrates that more precise forecast is accomplished by using the enhanced grey theory system scheme with weight table.

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