摘要
在构建径向基神经网络的基础上,通过对材料禁带宽度与太阳电池参数关系的研究,提出一种新的太阳电池通用仿真模型,该模型能自动调整参数,同时模拟不同太阳电池;通过遗传算法的优化,将预测技术应用于光伏发电系统,解决了蓄电池控制滞后的问题,提高了系统的稳定性。
Based on construction of radial basis function network, by studying relationship between materials band gaps and parameters of solar cells, a new solar general simulation model was offered, which can automatically ad-just the parameters and simulate different solar cells. By the optimization of genetic algorithm, the prediction tech-nology was used in photovoltaic power generation system to solve the problem of the lagging battery control, and the stability of photovohaic power generation system has been improved.
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2012年第11期1856-1862,共7页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(50803051)
湖南省教育厅重点项目(10A114)
湖南省自科基金重点项目(11JJ8004)
关键词
禁带宽度
太阳电池
遗传算法
预测技术
径向基神经网络
band gaps
solar cells
genetic algorithm
prediction technology
radial basis function network
