基于改进灰狼算法提取参数的光伏系统故障检测

Ahmed Faris Amiri, H. Oudira, A. Chouder
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引用次数: 0

摘要

准确可靠的故障检测程序是保证光伏发电系统正常运行的关键。为此,可信模型的使用是监测和监督所考虑的系统的重要步骤和必要工具。本文提出了一种基于三个主要步骤的建议程序。首先,利用改进的灰狼(MGW)算法对单二极管模型(ODM)的未知参数进行精确辨识;随后,基于提取的参数,对最大功率点模型的演化过程进行建模,并与实际并网MPP系统的测量结果进行了仿真。最后,利用PSIM™/Matlab™联合仿真对光伏阵列进行仿真,提取出MPP坐标,并实现了基于简单方法的高效故障检测流程。仿真结果表明,该方法在故障检测和诊断方面具有较好的实时性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Faults Detection of PV Systems Based on Extracted Parameters using Modified Grey Wolf Algorithm
Accurate and reliable fault detection procedures are crucial to ensure normal operation of photovoltaic (PV) systems. To this end, the use of trusted model is the major step and an essential tool for monitoring and supervision the system under consideration. In his paper a suggested procedure based on three main steps is presented. Firstly, the unknown parameters of the one diode model (ODM) are accurately identified using modified grey wolf (MGW) algorithm. Subsequently, based on the extracted parameters, the evolution of maximum power point model was modeled and simulated versus measurements of a grid connected real MPP system. Finally, the PV array is simulated to take out the MPP coordinates by using a PSIM™/Matlab™ co-simulation, as well as an efficient fault detection process based on simple approach is implemented. The obtain results show the effectiveness of this method in detecting and diagnosing faults for real time application.
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