电测与仪表Issue(11)：31-35,5.
基于双层 BP 神经网络的光伏电站输出功率预测
Photovoltaic power station output power prediction based on the double BP neural network
张立影 1孟令甲 2王泽忠1
作者信息
- 1. 华北电力大学电子与电子工程学院，北京102206
- 2. 石家庄铁道大学四方学院电气工程系，石家庄051132
- 折叠
摘要
Abstract
Photovoltaic power station output power has a great influence on power grid dispatching , but the photovolta-ic power station output power is random and uncontrollable due to the intensity of solar radiation and meteorological factors.In order to make reasonable use of the photovoltaic power generation system , a photovoltaic power station out-put power model based on weather forecast information and the BP neural network was proposed in the paper .The in-fluential factors of PV station output power were determined through correlation analysis .The model training and power prediction were processed by combination with historical data and meteorological factors .A new forecasting model , the double BP neural network model , was proposed in this paper .The predicted results of a photovoltaic power station were compared with the measured values .The results showed that the method could effectively improve the predictive accuracy of the PV station output power and had good reference values and practical values to power generation plan -ning.关键词
光伏电站/功率预测/双层BP神经网络/相关性/气象预测信息Key words
photovoltaic power station/power forecasting/double BP neural network/correlation/weather forecast in-formation分类
信息技术与安全科学引用本文复制引用
张立影,孟令甲,王泽忠..基于双层 BP 神经网络的光伏电站输出功率预测[J].电测与仪表,2015,(11):31-35,5.
