太阳能Issue(10)：21-26,6.DOI:10.19911/j.1003-0417.tyn20220225.01
气象条件对光伏电站日污秽损失率的影响分析
ANALYSIS OF INFLUENCE OF METEOROLOGICAL CONDITIONS ON DAILY POLLUTION LOSS RATE OF PV POWER STATIONS
杨旭 1喻聪 1龚旭1
作者信息
- 1. 中国电建集团贵州工程有限公司,贵阳 550003
- 折叠
摘要
Abstract
PV power generation uses the PV effect of semiconductors to directly convert solar energy into electrical energy. The deposition of dust in the air on the surface of PV modules will not only reduce the light energy transmitted to the PV modules，but also affect the heat dissipation of PV modules，thereby reducing the system efifciency of PV power stations，then affecting the power generation of PV power stations. This paper uses the combination of genetic algorithm and BP neural network (hereinafter referred to as“genetic algorithm BP neural network”) to model，analyze the impact of meteorological conditions on the daily pollution loss rate of the PV power station by inputting the wind speed，wind direction，relative humidity and ambient PM10 concentration. The test results show that the error of using the genetic algorithm BP neural network to predict the daily pollution loss rate of the PV power station can meet the accuracy requirements，and the error is reduced by 5.9% compared with the simple artificial neural network calculation. With the accumulation of dust，the daily pollution loss rate increases linearly with the growth of the cleaning cycle of PV modules，and the annual cleaning rate of PV modules surface decreases linearly. The genetic algorithm BP neural network can well predict the pollution loss rate caused by the meteorological environment，and the pollution loss rate of locally built PV power stations through the meteorological condition parameters.关键词
气象条件/光伏组件/遗传神经网络/日污秽损失率/污秽损失预测Key words
meteorological conditions/PV modules/genetic neural network/daily pollution loss rate/pollution loss prediction分类
信息技术与安全科学引用本文复制引用
杨旭,喻聪,龚旭..气象条件对光伏电站日污秽损失率的影响分析
[J].太阳能,2022,(10):21-26,6.
