IEEJ Transactions on Power and Energy
Online ISSN : 1348-8147
Print ISSN : 0385-4213
ISSN-L : 0385-4213
Special Issue Paper
Prediction of Next Day Solar Power Generation by Gray Theory and Neural Networks
Fujihiro YamadaYoshihiko WazawaKazuhiro KobayashiYasushi MiwaTomoki KinnoKazuto YukitaYasuyuki GotoKatsuhiro Ichiyanagi
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2014 Volume 134 Issue 6 Pages 494-500

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Abstract

This paper describes an application of a neural network that is method forecasting to time variation of insulation intensity. In recent years, research and technological developments in the field of electrical energy have focused on photovoltaic. Therefore, the photovoltaic power generator is introduced in large quantities in the power system in the future is expected. However, despite the high expectations for renewable power generation technologies, it remains difficult to obtain stable power from such distributed sources, primarily because they depend on weather conditions and other variable factors. In order to apply to the supply and demand stable operation, we report a case of developing a method for predicting solar power generation using the gray theory and a neural network.

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© 2014 by the Institute of Electrical Engineers of Japan
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