Modeling and Optimization of Wind Turbines in Wind Farms for Solving Multi-Objective Reactive Power Dispatch Using a New Hybrid Scheme

Rahmad Syah, Safoura Faghri, Mahyuddin KM Nasution, Afshin Davarpanah and Marek Jaszczur
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Rahmad Syah: Data Science & Computational Intelligence Research Group, Universitas Medan Area, Medan 20223, Indonesia
Safoura Faghri: School of Computer and Electrical Engineer, Graduate University of Research and Science, Islamic Azad University, Tehran 1584743311, Iran
Mahyuddin KM Nasution: Data Science & Computational Intelligence Research Group, Universitas Sumatera Utara, Medan 20154, Indonesia
Afshin Davarpanah: Data Science & Computational Intelligence Research Group, Universitas Medan Area, Medan 20223, Indonesia
Marek Jaszczur: Faculty of Energy and Fuels, AGH University of Science and Technology, Mickiewicza 30, 30059 Kraków, Poland

Energies, 2021, vol. 14, issue 18, 1-22

Abstract: Reactive Power Dispatch is one of the main problems in energy systems, particularly for the power industry, and a multi-objective framework should be proposed to solve it. In this study, we present a multi-objective framework for the optimization of wind turbines in wind farms. We investigate a new combined optimization method with Chaotic Local Search, Fuzzy Interactive Honey Bee Mating Optimization, Data-Sharing technique and Modified Gray Code for discrete variables. We use the proposed model to select optimal energy system parameters. The optimization process is based on simultaneous optimization of three functions. Finally, we improve a new method based on Pareto-optimal solutions to select the best one among all candidate solutions. The presented model and methodology are validated on energy systems with wind turbines. The evaluated efficiency is compared with the real system.

Keywords: MORPD problem; hybrid optimization; fuzzy theory; multi-objective; wind farms (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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