Development of Insolation Forecasting Method by Genetic Algorithm

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  • Kawasaki Shoji
    Department of Electronics and Bioinformatics School of Science and Technology, Meiji University
  • Taoka Hisao
    Graduate School of Electrical and Electronics Engineering, University of Fukui
  • Nagao Taiki
    Graduate School of Electrical and Electronics Engineering, University of Fukui
  • Onaka Keisuke
    Graduate School of Electrical and Electronics Engineering, University of Fukui

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Other Title
  • 遺伝的アルゴリズムによる日射量予測手法の開発
  • イデンテキ アルゴリズム ニ ヨル ニッシャリョウ ヨソク シュホウ ノ カイハツ

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Abstract

Renewable energy sources such as photovoltaic generation (PV) have been promoted to be innovated. However, the output of PV is influenced by the weather condition and cause a steep fluctuation. So it is important to forecast the output of PV when an electric power company makes the power supply schedule for demand. In this paper, the authors proposed a forecasting method for amount of insolation closely related to the output of PV. In the proposed method, the amount of insolation is forecasted through the application of Genetic Algorithm which is one of the optimization method by using the past measured data. In addition, the correlation coefficients are analyzed with the weather data and measured insolation data. And, the correlation coefficients are used as the weight of observe value. The authors verify the validity and prediction accuracy of the proposed method. Moreover, we tried to improve the forecasting error by using the latest measured weather data and weather data of the other point.

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