Support Vector Machine Based Voltage Relays for Voltage Disturbance Detection in Micro-Distribution Systems

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.

• Periodical: Applied Mechanics and Materials (Volumes 291-294)
• Pages: 2084-2090
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.291-294.2084
• Online since: February 2013
• Authors: Whei Min Lin, Chia Sheng Tu, Ting Chia Ou
• Keywords: Fuzzy Inference System (FIS), Micro-Distribution Systems (MDSs), Support Vector Machine (SVM)

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