リカレント型ニューラルネットワークを用いた風力発電機の３時間先出力電力予測

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  • Application of Recurrent Neural Network to 3-Hours-Ahead Generating Power Forecasting for Wind Power Generators
  • リカレントガタ ニューラル ネットワーク オ モチイタ フウリョク ハツデンキ ノ 3ジカンサキ シュツリョク デンリョク ヨソク

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Wind generators are rapidly gaining acceptance as some of the best alternative energy sources. However, wind speed is not constant and the power output of wind generators is proportional to the cube of the wind speed. In order to control the power output for wind power generators, it requires method of wind speed estimation. This paper proposes 3 hours ahead power output forecasting of wind generators based on wind speed forecasting by using Recurrent Neural Network (RNN). The validity of the proposed RNN is confirmed by comparing the forecasting abilities of feed-forward neural network (FFNN) and RNN in simulation results of 1∼3 hour ahead forecasting. The proposed method is not require complicated calculation.

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