光伏系统
日晒
人工神经网络
计算机科学
期限(时间)
电力系统
气象学
太阳能
功率(物理)
环境科学
工程类
人工智能
气候学
电气工程
量子力学
物理
地质学
作者
Atsushi Yona,Tomonobu Senjyu,Toshihisa Funabashi
出处
期刊:IEEE Power Engineering Society General Meeting
日期:2007-06-01
被引量:72
标识
DOI:10.1109/pes.2007.386072
摘要
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..
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