Support vector machine based voltage relays for voltage disturbance detection in micro-distribution systems

Whei Min Lin, Chia Sheng Tu, Ou Ting-Chia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study proposes combining fuzzy inference system and support vector machine based voltage relays for voltage disturbance detection in micro-distribution systems (MDSs). Moreover, the coordination characteristic curves of the trigger time versus dynamic errors are proposed for under-voltage and over-voltage protection. Modified coordination characteristic curves use a critical trigger time to isolate the faults. An support vector machine (SVM) is a multi-layer decision-making model, which detects voltage disturbances, such as voltage swell, voltage sag, voltage unbalance, and faults. Computer simulations are conducted, using an IEEE 30-bus power system and micro-distribution systems, to show the effectiveness of the proposed voltage relays.

Original languageEnglish
Title of host publicationAdvances in Energy Science and Technology
Pages2084-2090
Number of pages7
DOIs
Publication statusPublished - 2013
Event2012 International Conference on Sustainable Energy and Environmental Engineering, ICSEEE 2012 - Guangzhou, China
Duration: 2012 Dec 292012 Dec 30

Publication series

NameApplied Mechanics and Materials
Volume291-294
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2012 International Conference on Sustainable Energy and Environmental Engineering, ICSEEE 2012
Country/TerritoryChina
CityGuangzhou
Period12-12-2912-12-30

All Science Journal Classification (ASJC) codes

  • General Engineering

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