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Optimal reconfiguration of distribution system connected with distributed generations: A review of different methodologies

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  • Badran, Ola
  • Mekhilef, Saad
  • Mokhlis, Hazlie
  • Dahalan, Wardiah

Abstract

The Network Reconfiguration technique is a method which helps mitigate power losses from distribution systems. However, the reconfiguration technique can only do this up to a certain point. Further power loss reduction may be realized via the application of Distributed Generation (DG). However, the integration of DG into the distribution system at a non-optimal location may result in increased power losses and voltage fluctuations. Therefore, a strategy for the selection of optimal placement and sizing of the DG needs to be developed and at the same time ensure optimal configuration. Many heuristic and artificial intelligence methods have been proposed in the literature for optimal distribution network reconfiguration, DGs sizing, and location. This paper reviews some of the more recent methods for distribution network reconfiguration, DG placement, and sizing that are intended to minimize power losses and improve the voltage profile.

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  • Badran, Ola & Mekhilef, Saad & Mokhlis, Hazlie & Dahalan, Wardiah, 2017. "Optimal reconfiguration of distribution system connected with distributed generations: A review of different methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 854-867.
    • Handle: RePEc:eee:rensus:v:73:y:2017:i:c:p:854-867
    DOI: 10.1016/j.rser.2017.02.010
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    13. Mbuli, N. & Ngaha, W.S., 2022. "A survey of big bang big crunch optimisation in power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    14. Xiancheng Wang & Thiruvenkadam Srinivasan & Hyuntae Kim & In-ho Ra, 2020. "Exploration of DG Placement Strategy of Microgrids via FMFO Algorithm: Considering Increasing Power Demand and Diverse DG Combinations," Energies, MDPI, vol. 13(24), pages 1-24, December.
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    16. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
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    18. 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).
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