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Application of Recurrent Neural Network to Short-Term-Ahead Generating Power Forecasting for Photovoltaic System

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3 Author(s)
Yona, A. ; Dept. of Electr. & Electron. Eng., Ryukyus Univ., Okinawa ; Senjyu, T. ; Funabashi, T.

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 weather conditions. In order to predict the power output for PV system as accurate as possible, it requires method of insolation estimation. In this paper, a technique consider the insolation of each month, 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 use weather data..

Published in:

Power Engineering Society General Meeting, 2007. IEEE

Date of Conference:

24-28 June 2007