IEEJ Transactions on Power and Energy
Online ISSN : 1348-8147
Print ISSN : 0385-4213
ISSN-L : 0385-4213
Paper
Development of Insolation Forecasting Method by Genetic Algorithm
Shoji KawasakiHisao TaokaTaiki NagaoKeisuke Onaka
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2015 Volume 135 Issue 2 Pages 89-96

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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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© 2015 by the Institute of Electrical Engineers of Japan
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