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

概要

論文の詳細を見る
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.
社団法人電気学会の論文
2008-01-01