Mohd Herwan, Sulaiman and Zuriani, Mustaffa (2022) Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers. Results in Control and Optimization, 8 (100145). pp. 1-12. ISSN 2666-7207. (Published)
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Abstract
This paper proposes the implementation of various metaheuristic algorithms in solving the optimal power flow (OPF) with the presence of Flexible AC Transmission System (FACTS) devices in the power system. OPF is one of the well-known problems in power system operations and with the inclusion of the FACTS devices allocation problems into OPF will make the solution more complex. Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. These algorithms are selected from the different metaheuristics classification groups, where the implementation of these algorithms into the said problems will be tested on the modified IEEE 14-bus system. From the simulation results, it is suggested that TLBO and HBO perform better compared to the rest of algorithms.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Cost minimization; FACTS devices; Loss minimization; Metaheuristic algorithms; Optimal power flow |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Computing Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 23 Aug 2023 01:26 |
| Last Modified: | 23 Aug 2023 01:26 |
| URI: | http://umpir.ump.edu.my/id/eprint/37450 |
| Download Statistic: | View Download Statistics |
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