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A Multi-Objective Optimization Problem for Optimal Site Selection of Wind Turbines for Reduce Losses and Improve Voltage Profile of Distribution Grids

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  • Amirreza Naderipour

    (Institute of High Voltage & High Current, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor 81310, Malaysia)

  • Zulkurnain Abdul-Malek

    (Institute of High Voltage & High Current, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor 81310, Malaysia)

  • Saber Arabi Nowdeh

    (Electrical Department, Payambar’azam Student Research Center, Golestan 87349-49318, Iran)

  • Foad H. Gandoman

    (Research Group MOBI—Mobility, Logistics, and Automotive Technology Research Center, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium
    Flanders Make, 3001 Heverlee, Belgium)

  • Mohammad Jafar Hadidian Moghaddam

    (College of Engineering and Science, Victoria University, Melbourne 3047, Australia)

Abstract

In this paper, the optimal site and size selection of wind turbines (WTs) is presented considering the maximum allowable capacity constraint with the objective of loss reduction and voltage profile improvement of distribution grids based on particle swarm optimization (PSO as a multi-objective problem using weighted coefficients method. The optimal site, size, and power factor of the WTs are determined using PSO. The proposed method is implemented on 84- and 32-bus standard grids. In this study, PSO algorithm is applied to determine the size, site, and power factor of WTs considering their maximum size constraint (with constraint, variant size) and also not considering their maximum size constraint (without constraint, constant size). The simulation results showed that the PSO is effective to find the site, size, and power factor of WTs optimally in the single and multi-objective problem. The results of this method showed that the power loss is reduced more and voltage profile improved more considering WTs maximum allowable size versus not considering this constraint. Additionally, the multi-objective results showed that there is a compromise between the objectives in the multi-objective WTs site selection and the multi-objective problem solution is a more realistic and accurate approach in comparison with the single-objective problem solution.

Suggested Citation

  • Amirreza Naderipour & Zulkurnain Abdul-Malek & Saber Arabi Nowdeh & Foad H. Gandoman & Mohammad Jafar Hadidian Moghaddam, 2019. "A Multi-Objective Optimization Problem for Optimal Site Selection of Wind Turbines for Reduce Losses and Improve Voltage Profile of Distribution Grids," Energies, MDPI, vol. 12(13), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2621-:d:246542
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    References listed on IDEAS

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    2. Jing Yang & Jiale Xiong & Yen-Lin Chen & Por Lip Yee & Chin Soon Ku & Manoochehr Babanezhad, 2023. "Improved Golden Jackal Optimization for Optimal Allocation and Scheduling of Wind Turbine and Electric Vehicles Parking Lots in Electrical Distribution Network Using Rosenbrock’s Direct Rotation Strat," Mathematics, MDPI, vol. 11(6), pages 1-23, March.
    3. Anderson Passos de Aragão & Patrícia Teixeira Leite Asano & Ricardo de Andrade Lira Rabêlo, 2020. "A Reservoir Operation Policy Using Inter-Basin Water Transfer for Maximizing Hydroelectric Benefits in Brazil," Energies, MDPI, vol. 13(10), pages 1-26, May.
    4. Feng, Li & Liu, Jiajun & Lu, Haitao & Liu, Bingzhi & Chen, Yuning & Wu, Shenyu, 2022. "Robust operation of distribution network based on photovoltaic/wind energy resources in condition of COVID-19 pandemic considering deterministic and probabilistic approaches," Energy, Elsevier, vol. 261(PB).
    5. Sun, Hongyue & Ebadi, Abdol Ghaffar & Toughani, Mohsen & Nowdeh, Saber Arabi & Naderipour, Amirreza & Abdullah, Aldrin, 2022. "Designing framework of hybrid photovoltaic-biowaste energy system with hydrogen storage considering economic and technical indices using whale optimization algorithm," Energy, Elsevier, vol. 238(PA).
    6. Gorg Abdelmassih & Mohammed Al-Numay & Abdelali El Aroudi, 2021. "Map Optimization Fuzzy Logic Framework in Wind Turbine Site Selection with Application to the USA Wind Farms," Energies, MDPI, vol. 14(19), pages 1-15, September.

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