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A computational method based on Gustafson‐Kessel fuzzy clustering for a novel islanding detection for grid connected devices and sensors
Computational Intelligence ( IF 1.8 ) Pub Date : 2020-03-05 , DOI: 10.1111/coin.12311
B. Ponmudi 1 , G. Balasubramanian 2
Affiliation  

Fuzzy Clustering‐based (G‐K) Gustafson‐Kessel is used to create the fuzzy rule‐based classifier in a grid connected photovoltaic (PV) system where it is tested using specific features in a grid connected PV inverter for detecting islanding condition. It is detected when harmonic content of voltages at the Point of Common Coupling and inverter increases beyond a threshold value. If islanding is not detected, distribution lines are rendered unsafe. The present study uses G‐K fuzzy clustering to categorize islanding and nonislanding incidents. Two features based on Total Harmonic Distortion are extracted and used as inputs for the G‐K fuzzy clustering classifier. The proposed technique is tested using nonlinear loads and its performance is verified by simulation using MATLAB Simulink. A hardware test set‐up is developed to validate the proposed antiislanding technique and the results obtained are discussed.

中文翻译:

基于 Gustafson-Kessel 模糊聚类的并网设备和传感器孤岛检测计算方法

基于模糊聚类 (G-K) 的 Gustafson-Kessel 用于在并网光伏 (PV) 系统中创建基于模糊规则的分类器,其中使用并网光伏逆变器中的特定特征对其进行测试,以检测孤岛状况。当公共耦合点和逆变器的电压谐波含量增加超过阈值时检测到。如果没有检测到孤岛,配电线路就会变得不安全。本研究使用 G-K 模糊聚类对孤岛和非孤岛事件进行分类。提取基于总谐波失真的两个特征并将其用作 G-K 模糊聚类分类器的输入。所提出的技术使用非线性负载进行测试,并通过使用 MATLAB Simulink 进行仿真验证其性能。
更新日期:2020-03-05
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