Issue |
E3S Web Conf.
Volume 152, 2020
2019 International Conference on Power, Energy and Electrical Engineering (PEEE 2019)
|
|
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Article Number | 03002 | |
Number of page(s) | 5 | |
Section | Power Electronics and Transmission Technology | |
DOI | https://doi.org/10.1051/e3sconf/202015203002 | |
Published online | 14 February 2020 |
Optimal TCSC Allocation via Chaotic Immune Symbiotic Organisms Search for Voltage Profile Improvement
1,2,3,5,7
Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
4,6
College of Engineering, Universiti Tenaga Nasional, Kajang, Selangor, Malaysia
* Corresponding author: ismailbm1@gmail.com
As the load demand in a power system increases, power system operators struggle to maintain the power system to be operated within its acceptable limits. If no mitigation actions are taken, a power system may suffer from voltage collapse, which in turn leads to blackout. Flexible AC Transmission System (FACTS) devices can be employed to help improve the voltage profile of the power system. This paper presents the implementation of Chaotic Immune Symbiotic Organism Search (CISOS) optimization technique to solve optimal Thyristor Controlled Series Compensator (TCSC) in a power system for voltage profile improvement. Validation process are conducted on IEEE 26-bus RTS resulting in the capability of CISOS in solving the allocation problem with a better voltage profile. Comparative studies conducted with respect to Particle Swarm Optimization (PSO) and Evolutionary Programming (EP) has revealed the superiority of CISOS over PSO and EP in solving the optimal allocation problem by producing optimal solution with a better voltage profile. The results and information obtained from this study can help power system operator in terms of optimal compensation in power system as well as improving the operation of a power system.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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