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PHOTOVOLTAIC ARRAY FAULT DIAGNOSIS METHOD BASED ON IMPROVED RANDOM FOREST ALGORITHM

机译:基于改进的随机森林算法的光伏阵列故障诊断方法

摘要

Disclosed is a photovoltaic array fault diagnosis method based on an improved random forest algorithm, relating to the field of photovoltaic technology. In the method, a running state of each branch in a photovoltaic array is reflected by means of parameters of a main trunk and each branch of the photovoltaic array, and a running state of each photovoltaic cell assembly in the branch is reflected by means of a voltage difference between arrays among different branches, so as to realize fault location of the photovoltaic array; and by optimizing and improving the three parts, i.e. decision tree weighting and voting, tie processing and the importance measurement of fault features, by means of out-of-package samples, the accuracy of the fault diagnosis can be higher and the reliability of the fault diagnosis can be stronger.
机译:一种基于改进的随机森林算法的光伏阵列故障诊断方法,涉及光伏技术领域。在该方法中,通过光伏阵列的主干线和每个分支的参数来反映光伏阵列中的每个分支的运行状态,并且通过光伏电池组件中的每个光伏电池组件的运行状态来反映。不同分支之间的阵列之间的电压差,以实现光伏阵列的故障定位;通过优化和改进决策树的权重和投票,平局处理和故障特征的重要性测量这三个部分,可以通过外包装样本来提高故障诊断的准确性和可靠性。故障诊断可以更强。

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