Insolation Forecasting Method Using NN with EPSO in Consideration of Correlation between Other Regions

Abstract

Recently, there is a movement that aims to realize a distributed energy system in Japan. The PV (photovoltaic) generation is especially expected, and it is anticipated that interconnection number of PVs will increase more and more in the future. However, an amount of insolation is easily affected by the weather, the output of PV and the supply of electricity becomes unstable. And it causes various problems in a distribution system. Therefore, it is important to forecast the amount of insolation. In previous study, MLPNN (multilayer perceptron neural network) is a general method to forecast the amount of insolation. However, it is in danger of falling into a local solution by only MLPNN. In this study, the authors propose a forecasting method of amount of insolation using MLPNN and EPSO (evolutionary particle swarm optimization). The authors use EPSO in addition to MLPNN to solve the problem. The authors also propose a forecasting method of amount of insolation using other regions weather data for the accuracy improvement.