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Simultaneous fault detection algorithm for grid-connected photovoltaic plants

机译:并网光伏电站的同时故障检测算法

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In this work, the authors present a new algorithm for detecting faults in grid-connected photovoltaic (GCPV) plant. There are few instances of statistical tools being deployed in the analysis of photovoltaic (PV) measured data. The main focus of this study is, therefore, to outline a PV fault detection algorithm that can diagnose faults on the DC side of the examined GCPV system based on the t-test statistical analysis method. For a given set of operational conditions, solar irradiance and module temperature, a number of attributes such as voltage and power ratio of the PV strings are measured using virtual instrumentation (VI) LabVIEW software. The results obtained indicate that the fault detection algorithm can detect accurately different types of faults such as, faulty PV module, faulty PV String, faulty Bypass diode and faulty maximum power point tracking unit. The proposed PV fault detection algorithm has been validated using 1.98 kWp PV plant installed at the University of Huddersfield, UK.
机译:在这项工作中,作者提出了一种用于检测并网光伏(GCPV)工厂故障的新算法。在光伏(PV)测量数据的分析中很少部署统计工具。因此,本研究的主要重点是概述一种PV故障检测算法,该算法可以基于 t 测试统计分析方法来诊断所检查GCPV系统的直流侧的故障。对于给定的一组工作条件,太阳辐照度和模块温度,使用虚拟仪器(VI)LabVIEW软件测量了许多属性,例如PV串的电压和功率比。所得结果表明,该故障检测算法可以准确地检测出不同类型的故障,例如有故障的光伏组件,有故障的光伏组串,有故障的旁路二极管和有故障的最大功率点跟踪单元。拟议的光伏故障检测算法已使用英国哈德斯菲尔德大学安装的1.98 kWp光伏电站进行了验证。

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