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Assessment of optimization algorithms capability in distribution network planning: Review, comparison and modification techniques

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  • Sedghi, Mahdi
  • Ahmadian, Ali
  • Aliakbar-Golkar, Masoud

Abstract

Optimal expansion of medium-voltage power networks because of load growth is a combinatorial problem which is important from technical and economic points of view. The planning solutions consist of installation and/or reinforcement of high voltage/medium voltage (HV/MV) substations, feeder sections, distributed generation (DG) and storage units to expand the capacity of the network. The cost objective function of the system should be minimized subject to the technical constraints. Due to the complicacy and the complexity of the problem, it should be solved by modern optimization algorithms. In this paper, the most famous optimization algorithms for solving the distribution network planning problem are reviewed and compared, and some points are proposed to improve the performance of the algorithms. In order to compare the algorithms in practice, and verify the proposed improvement points, the numerical studies on three test distribution networks are presented. The results show that every algorithm has its own advantages and disadvantages in specific conditions. However, in general manner, the hybrid Tabu search/genetic algorithm (TS/GA) and the improved particle swarm optimization (PSO) algorithm proposed in this paper are the best choices for optimal distribution network planning.

Suggested Citation

  • Sedghi, Mahdi & Ahmadian, Ali & Aliakbar-Golkar, Masoud, 2016. "Assessment of optimization algorithms capability in distribution network planning: Review, comparison and modification techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 415-434.
    • Handle: RePEc:eee:rensus:v:66:y:2016:i:c:p:415-434
    DOI: 10.1016/j.rser.2016.08.027
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    3. Syed Ali Abbas Kazmi & Hafiz Waleed Ahmad & Dong Ryeol Shin, 2019. "A New Improved Voltage Stability Assessment Index-centered Integrated Planning Approach for Multiple Asset Placement in Mesh Distribution Systems," Energies, MDPI, vol. 12(16), pages 1-41, August.
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    5. Saboori, Hedayat & Hemmati, Reza & Ghiasi, Seyyed Mohammad Sadegh & Dehghan, Shahab, 2017. "Energy storage planning in electric power distribution networks – A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1108-1121.
    6. Xiang, Yue & Dai, Jiakun & Xue, Ping & Liu, Junyong, 2023. "Autonomous topology planning for distribution network expansion: A learning-based decoupled optimization method," Applied Energy, Elsevier, vol. 348(C).
    7. Candas, Soner & Reveron Baecker, Beneharo & Mohapatra, Anurag & Hamacher, Thomas, 2023. "Optimization-based framework for low-voltage grid reinforcement assessment under various levels of flexibility and coordination," Applied Energy, Elsevier, vol. 343(C).
    8. Syed Ali Abbas Kazmi & Dong Ryeol Shin, 2017. "DG Placement in Loop Distribution Network with New Voltage Stability Index and Loss Minimization Condition Based Planning Approach under Load Growth," Energies, MDPI, vol. 10(8), pages 1-28, August.
    9. Papadimitrakis, M. & Giamarelos, N. & Stogiannos, M. & Zois, E.N. & Livanos, N.A.-I. & Alexandridis, A., 2021. "Metaheuristic search in smart grid: A review with emphasis on planning, scheduling and power flow optimization applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    10. Ahmadian, Ali & Sedghi, Mahdi & Fgaier, Hedia & Mohammadi-ivatloo, Behnam & Golkar, Masoud Aliakbar & Elkamel, Ali, 2019. "PEVs data mining based on factor analysis method for energy storage and DG planning in active distribution network: Introducing S2S effect," Energy, Elsevier, vol. 175(C), pages 265-277.
    11. Stavros Lazarou & Vasiliki Vita & Lambros Ekonomou, 2018. "Protection Schemes of Meshed Distribution Networks for Smart Grids and Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-17, November.
    12. Nevena Srećković & Miran Rošer & Gorazd Štumberger, 2021. "Utilization of Active Distribution Network Elements for Optimization of a Distribution Network Operation," Energies, MDPI, vol. 14(12), pages 1-17, June.
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