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Graduate Studies

Adaptive Simplified Neuro-Fuzzy Controller as Supplementary Stabilizer for SVC

Abstract

dc:description.abstract

A simplified version of an Adaptive Neuro-Fuzzy Controller (ANFC) applied to a FACTS device, namely a Static VAr Compensator (SVC), is presented in this dissertation. The proposed Adaptive Simplified Neuro-Fuzzy Controller (ASNFC), used as a supplementary controller to damp power system oscillations, consists of a reduced number of input Membership Functions (MFs) and Consequent Parameters (CPs). Unlike the common techniques of using the generator speed or the power angle deviations as inputs to the controller, the input to the ASNFC is the power deviation at the bus where the SVC is located. A Neuro Identifier is used to track the behaviour of the system in real-time and update the controller on-line. The effectiveness of the proposed controller is tested on a single machine infinite bus system, and a multi-machine system. Results of simulation studies demonstrate that the performance with the proposed ASNFC is practically the same as with ANFC, but with a smaller number of parameters to optimize that reduces computation time for real-time application. In addition, the proposed ASNFC is further tested on a physical model power system where the controller is applied to the generation unit. The results obtained indicate a successful implementation of the ASNFC in damping power system oscillations over the Conventional Power System Stabilizer (CPSS). Furthermore, similar dynamic performance is provided by the ASNFC, as compared to the detailed ANFC.

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Grantor dc:publisher.institution
Graduate Studies
Year dc:date.issued
2014

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • AlBakkar, Anas
Advisor dc:contributor.advisor
  • Malik, O.P.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:ucalgary.scholaris.ca:11023/1950

Chain of custody

source
Harvested from
University of Calgary
Base URL
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Last updated
2026-07-24
Source record
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citation

AlBakkar, Anas. Adaptive Simplified Neuro-Fuzzy Controller as Supplementary Stabilizer for SVC. Graduate Studies, 2014. http://hdl.handle.net/11023/1950