基于禁带宽度的太阳电池建模及智能预测技术研究  

MODELING OF SOLAR CELLS BASED ON BAND GAPS AND STUDIES OF INTELLIGENT PREDICTION TECHNOLOGY

作　　者：易灵芝[1] 刘珊[1] 邓栋[1] 姚哲之[1] 周珍珍[1] 龚会茹[1] 

机构地区：[1]湘潭大学信息工程学院,湘潭411105

出　　处：《太阳能学报》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)

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.

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 

分 类 号：TB611[一般工业技术—制冷工程]