Volume 9, Issue 2 (June 2013)                   IJEEE 2013, 9(2): 94-106 | Back to browse issues page

XML Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Bakhshi M, Noroozian R, Gharehpetian G. Islanding Detection of Synchronous Machine-Based DGs using Average Frequency Based Index. IJEEE 2013; 9 (2) :94-106
URL: http://ijeee.iust.ac.ir/article-1-548-en.html
Islanding Detection of Synchronous Machine-Based DGs using Average Frequency Based Index
M. Bakhshi , R. Noroozian , G. Gharehpetian
Abstract:   (6813 Views)
Identification of intentional and unintentional islanding situations of dispersed generators (DGs) is one of the most important protection concerns in power systems. Considering safety and reliability problems of distribution networks, an exact diagnosis index is required to discriminate the loss of the main network from the existing parallel operation. Hence, this paper introduces a new islanding detection method for synchronous machine–based DGs. This method uses the average value of the generator frequency to calculate a new detection index. The proposed method is an effective supplement of the over/under frequency protection (OFP/UFP) system. The analytical equations and simulation results are used to assess the performance of the proposed method under various scenarios such as different types of faults, load changes and capacitor bank switching. To show the effectiveness of the proposed method, it is compared with the performance of both ROCOF and ROCOFOP methods.
Keywords: Islanding Detection , Non-Detection Zone , Passive Methods , Synchronous Machine-Based Distributed Generation
Full-Text [PDF 2938 kb]   (3338 Downloads)    
Type of Study: Research Paper | Subject: Distributed Generation
Received: 2013/01/24 | Revised: 2014/10/08 | Accepted: 2013/06/26
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.