Fuzzy Elman-DIOC Neural Network Prediction and Analysis of Short-Term Photovoltaic Power
In order to improve the efficiency of short term photovoltaic power prediction,a short term photovoltaic power predic-tion method based on Elman neural network is designed.On the basis of determining the network structure and parameters to achieve accurate prediction,the method after training shows high accuracy and rationality.The results show that:the data of class cluster express great similarity,and the data of class cluster show obvious difference characteristics.The optimized method is used to predict the power generation,and the relationship between the predicted value and the measured value is established.The predicted result is close to the measured value on the forecast day,and the optimized clustering algorithm is used to obtain more accurate prediction results.After the optimization of the algorithm in this paper,the mean value of prediction errors decreased sig-nificantly,and the mean value of IMSE decreased by about 80%,and more effective clustering results were obtained.The optimi-zation clustering processing could promote the effective improvement of short-term prediction accuracy.This research can be ex-tended to other similar fields and has good practical value.
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