摘要
提出一种简单实用的光伏组件建模方法,即由光伏组件参数得到光伏电池单元参数,根据光伏组件内部光伏电池单元故障情况,得到等效的光伏组件故障模型。选取光伏组件的特征参数,通过光伏组件等效模型获取故障数据。在Matlab中建立BP神经网络模型,使用BP网络对光伏组件内部故障进行诊断。仿真试验表明所选特征量合理,在保证精度的前提下,使用本文的方法能有效地对光伏组件内部故障进行诊断。
This paper proposes a simple and practical PV module modeling approach. Namely, the parameters of photovohaic cell are obtained by the parameters of the PV module; according to the internal photovoltaic ceils malfunction of the photovohaic module, the fault model of equivalent photovohaic module is obtained; selecting the characteristic parameters of the PV module, the fault data is obtained by the equivalent model of the PV module. The BP neural network model is established in Matlab and used to diagnose the internal faults of the PV module. The simulation experiment shows that the selected characteristic is reasonable, and the internal faults of the PV module can be effectively diagnosed by using the proposed method in the premise of ensuring the accuracy.
出处
《陕西电力》
2016年第2期15-21,共7页
Shanxi Electric Power
基金
国家自然科学基金资助项目(51207044)
关键词
光伏组件
故障类型
故障模型
BP神经网络
特征参数
photovoltaic module
fault type
fault model
BP neural network
characteristic parameter
