Mohd Herwan, Sulaiman and Zuriani, Mustaffa (2024) Hyper-heuristic strategies for optimal power flow problem with FACTS devices allocation in wind power integrated system. Results in Control and Optimization, 14 (100373). pp. 1-21. ISSN 2666-7207. (Published)
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Abstract
This research provides hyper-heuristic methodologies for solving Optimal Power Flow (OPF) issues in power system networks with Flexible AC Transmission Systems (FACTS) devices. OPF can be treated as one of the demanding challenges in the power system operating networks. To address the problems of loss and cost reduction, three types of FACTS devices will be studied in this paper: Static VAR Compensator (SVC), Thyristor-Controlled Series Compensator (TCSC), and Thyristor-Controlled Phase Shifter (TCPS). Two high level hyper-heuristic (HHH) approaches, called Exponential Monte Carlo with counter (EMCQ) and randomly select-Only Improving (OI), are employed as high-level metaheuristic to select and leverage the effectiveness of four low-level metaheuristics (LLH). These low-level metaheuristics comprise the Moth-Flame Optimizer (MFO), Barnacles Mating Optimizer (BMO), Teaching-Learning Based Optimization (TLBO) and Gradient-Based Optimizer (GBO). The usage of HHH solving the OPF problem is tested on the modified IEEE 30 bus system that integrates the thermal generators with the wind power. Findings of the study demonstrated the promising results by HHH which manages to outperform all the selected LLH algorithms.
| Item Type: | Article |
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| Additional Information: | Indexed by Scopus |
| Uncontrolled Keywords: | Optimal power flow; Reactive power; Particle swarm optimization |
| 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) |
| Faculty/Division: | Faculty of Computing Faculty of Electrical and Electronic Engineering Technology |
| Depositing User: | Mr Muhamad Firdaus Janih@Jaini |
| Date Deposited: | 28 May 2024 08:12 |
| Last Modified: | 28 May 2024 08:12 |
| URI: | http://umpir.ump.edu.my/id/eprint/40979 |
| Download Statistic: | View Download Statistics |
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