415 ニューラルネットワークを用いたバイオエタノール・ソーラー改質システムの運用予測(新エネルギー(2),環境保全型エネルギー技術)

概要

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The bioethanol reforming system (FBSR) using sunlight as a heat source is a fuel production system for fuel cells with little environmental impact. However, because solar radiation and outside air temperature are unstable, it is difficult to predict operation of the system with accuracy. Therefore, an operation prediction program of the FBSR using a layered neural network (NN) with the error-correction learning method has been developed. We developed a method of analyzing the operation of a natural energy system with sufficient accuracy. The weather pattern (the amount of global solar radiation and the outside air temperature) and energy-demand pattern for the past one year are inputted into the NN. As a result of analyzing using the developed algorithm, when ± 20% or less of power load fluctuation occurred, the operation plan was analyzable in 14% or less of error span.
社団法人日本機械学会の論文
2008-07-09