A computational method based on Gustafson‐Kessel fuzzy clustering for a novel islanding detection for grid connected devices and sensors. (5th March 2020)

• Record Type: Journal Article
• Authors: Ponmudi, B.; Balasubramanian, G.
• Is Part Of: Computational intelligence. Volume 36:Number 4(2020)
• Page Start: 1723
• Page End: 1736
• Publication Date: 2020-03-05
• Subjects: fuzzy clustering -- Gustafson‐Kessel -- point of common coupling (PCC) -- total harmonic distortion (THD); Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12311
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract: 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.