POWER GENERATION FORECASTING MODEL FOR PHOTOVOLTAIC ARRAY BASED ON GENERIC ALGORITHM AND BP NEURAL NETWORK

被引：0
|
作者：
Yang, Zhengqiu [1 ]
Cao, Yapei [1 ]
Xiu, Jiapeng [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Beijing 100876, Peoples R China
来源：
2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems (CCIS) | 2014年
关键词：
Photovoltaic generation (PV); Short-term forecasting; BP Neural network; Genetic algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
High concentration photovoltaic is a new type of solar power generation mode, which has better photoelectric conversion rate but is more vulnerable to weather factors. Therefore, accurate and efficient forecasting methods have important significance of increasing the security and stability of the solar power station. This paper focuses on the short-term forecasting method which aims at forecasting power generation in five minutes. This paper uses BP neural network(BP-NN) as the basic forecasting model and applies generic algorithm(GA) to optimize the weights and thresholds of BP-NN. The experimental results show that, the prediction effect of this method is ideal.
引用
收藏
页码：380 / 383
页数：4
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