A new artificial neural network based method for islanding detection of distributed generators

Author(s)

Merlin, V. L. ^[1] ; Santos, R. C. ^[1] ; Grilo, A. P. ^[1] ; Vieira, J. C. M. ^[2] ; Coury, D. V. ^[2] ; Oleskovicz, M. ^[2]

Affiliation

^[1] Fed Univ ABC, BR-09210580 Santo Andre, SP - Brazil

^[2] Univ Sao Paulo, Sch Engn Sao Carlos, BR-13566590 Sao Carlos, SP - Brazil

• Document type: Journal article
• Source: INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS; v. 75, p. 139-151, FEB 2016.
• Web of Science Citations: 20

Abstract

This paper presents an artificial neural network (ANN) based method for islanding detection of distributed synchronous generators. The proposed method takes advantage of ANN as pattern classifiers. It is capable of identifying the islanding condition based on samples of the voltage waveform measured at the distributed generator terminals only, which is an important advantage over other ANN-based anti-islanding methods. Moreover, the proposed method is robust against false operation. In order to create a training data set for the ANN, a data selection procedure has been proposed, so that the ANN could be trained more effectively, which has contributed positively to the good performance of the method. The concept of the time-performance region has been introduced to assess the method performance, as well as the non-detection zones. A detailed discussion about the data sampling rate to feed the proposed method has also been conducted, so that the computational burden can be faced as an important factor to assess its performance. (C) 2015 Elsevier Ltd. All rights reserved. (AU)

• FAPESP's process: 10/01690-2 - Technological development for protection, analysis, supervision and automation of electrical power systems of the future
• Grantee: Denis Vinicius Coury
• Support Opportunities: Research Projects - Thematic Grants