電気学会論文誌B(電力・エネルギー部門誌)
Online ISSN : 1348-8147
Print ISSN : 0385-4213
ISSN-L : 0385-4213
特集論文
ニューラルネットワークを用いた太陽光発電設備の24時間先発電電力予測
與那 篤史千住 智信舟橋 俊久関根 秀臣
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2008 年 128 巻 1 号 p. 33-39

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In recent years, there have been focus on environmental pollution issue resulting from consumption of fuel, e.g., coal and oil. Thus, introduction of an alternative energy source such as solar energy is expected. However, insolation is not constant and output of photovoltaic (PV) system is influenced by meteorological conditions. In order to predict the power output for PV system as accurate as possible, it requires method of insolation estimation. In this paper, the authors take the insolation of each month into consideration, and confirm the validity of using neural network to predict insolation by computer simulations. The proposed method in this paper does not require complicated calculation and mathematical model with only meteorological data.
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© 電気学会 2008
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