Influenced by meteorological factors such as light intensity

temperature

humidity and wind speed

the output of photovoltaic power generation system has the characteristics of fluctuation

indirectness and uncontrollable

the forecast results of photovoltaic power prediction has low accuracy.To solve this problem

this paper combines the fuzzy theory with support vector machine(SVM)method to predict the photovoltaic power generation.Firstly

the fuzzy membership degree value is calculated by the fuzzy Cmeans clustering algorithm.Then

the original sample is clustered to generate the fuzzy sample.Secondly

the support vector machine is applied to train the fuzzy sample.Finally

the FSVM forecast model is employed to predict the next few days' photovoltaic power capacity.The MATLAB experimental results show that

the accuracy of the model is higher compared with the BP and SVM model.The FSVM model can overcome the conventional troubles such as easily going into the minimum problem and uncertain meterorological factors.