Chaos embedded symbiotic organisms search technique for optimal FACTS device allocation for voltage profile and security improvement

Due to the ever-increasing energy demand, power system operators have attempted to cope with these demands while keeping the power system remain operable. Economic constraints have forced the power system operator to abandon their effort in expanding the power system. The increased load demand can c...

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Bibliographic Details
Published in:Indonesian Journal of Electrical Engineering and Computer Science
Main Author: Mohamad Zamani M.K.; Musirin I.; Suliman S.I.; Bouktir T.
Format: Article
Language:English
Published: Institute of Advanced Engineering and Science 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037637491&doi=10.11591%2fijeecs.v8.i1.pp146-153&partnerID=40&md5=901bf61a57f892fc59e55a6253dbea1c
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Summary:Due to the ever-increasing energy demand, power system operators have attempted to cope with these demands while keeping the power system remain operable. Economic constraints have forced the power system operator to abandon their effort in expanding the power system. The increased load demand can cause the power system to suffer from voltage instability and voltage collapse, especially during contingency condition. Hence, a strategy is required to maintain the steady state operation of a power system. Various research has been conducted to tackle this problem. Therefore, this paper presents the implementation of Chaos Embedded Symbiotic Organisms Search technique to solve optimal FACTS device allocation problem in power transmission system. Various practical constraints are also considered in the optimisation process to emulate the real-life constraints in power system. The optimisation process is conducted on a 26-bus IEEE RTS has validated that the results obtained has not violated the power system stability. The results provided by the proposed optimisation technique has successfully improved the voltage profile and voltage security in the system. Comparative studies are also conducted involving Particle Swarm Optimization and Evolutionary Programming technique resulting good results agreement and superiority of the proposed technique. Results obtained from this study would be beneficial to the power system operators regarding optimisation in power system operation for the implementation in real power transmission network. © 2017 Institute of Advanced Engineering and Science. All rights reserved.
ISSN:25024752
DOI:10.11591/ijeecs.v8.i1.pp146-153