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Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distribution systems

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  • Sedighizadeh, Mostafa
  • Esmaili, Masoud
  • Esmaeili, Mobin

Abstract

In this paper, a multi-objective framework is proposed for simultaneous optimal network reconfiguration and DG (distributed generation) power allocation. The proposed method encompasses objective functions of power losses, voltage stability, DG cost, and greenhouse gas emissions and it is optimized subject to power system operational and technical constraints. In order to solve the optimization problem, the HBB-BC (Hybrid Big Bang-Big Crunch) algorithm as one of the most recent heuristic tools is modified and employed here by introducing a mutation operator to enhance its exploration capability. To resolve the scaling problem of differently-scaled objective functions, a fuzzy membership is used to bring them into a same scale and then, the fuzzy fitness of the final objective function is utilized to measure the satisfaction level of the obtained solution. The proposed method is tested on balanced and unbalanced test systems and its results are comprehensively compared with previous methods considering different scenarios. According to results, the proposed method not only offers an enhanced exploration capability but also has a better converge rate compared with previous methods. In addition, the simultaneous network reconfiguration and DG power allocation leads to a more optimal result than separately doing tasks of reconfiguration and DG power allocation.

Suggested Citation

  • Sedighizadeh, Mostafa & Esmaili, Masoud & Esmaeili, Mobin, 2014. "Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distribution systems," Energy, Elsevier, vol. 76(C), pages 920-930.
    • Handle: RePEc:eee:energy:v:76:y:2014:i:c:p:920-930
    DOI: 10.1016/j.energy.2014.09.004
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    References listed on IDEAS

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    5. Mukhopadhyay, Bineeta & Das, Debapriya, 2020. "Multi-objective dynamic and static reconfiguration with optimized allocation of PV-DG and battery energy storage system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    6. Jordehi, A. Rezaee, 2015. "Optimisation of electric distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1088-1100.
    7. Das, Bikash & Mukherjee, V. & Das, Debapriya, 2019. "Optimum DG placement for known power injection from utility/substation by a novel zero bus load flow approach," Energy, Elsevier, vol. 175(C), pages 228-249.
    8. Anh Viet Truong & Trieu Ngoc Ton & Thuan Thanh Nguyen & Thanh Long Duong, 2018. "Two States for Optimal Position and Capacity of Distributed Generators Considering Network Reconfiguration for Power Loss Minimization Based on Runner Root Algorithm," Energies, MDPI, vol. 12(1), pages 1-16, December.
    9. Luis A. Gallego Pareja & Jesús M. López-Lezama & Oscar Gómez Carmona, 2022. "A Mixed-Integer Linear Programming Model for the Simultaneous Optimal Distribution Network Reconfiguration and Optimal Placement of Distributed Generation," Energies, MDPI, vol. 15(9), pages 1-26, April.
    10. 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).
    11. Li, Peng & Ji, Jie & Ji, Haoran & Song, Guanyu & Wang, Chengshan & Wu, Jianzhong, 2020. "Self-healing oriented supply restoration method based on the coordination of multiple SOPs in active distribution networks," Energy, Elsevier, vol. 195(C).
    12. Das, Sangeeta & Das, Debapriya & Patra, Amit, 2017. "Reconfiguration of distribution networks with optimal placement of distributed generations in the presence of remote voltage controlled bus," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 772-781.
    13. Zeng, Bo & Wen, Junqiang & Shi, Jinyue & Zhang, Jianhua & Zhang, Yuying, 2016. "A multi-level approach to active distribution system planning for efficient renewable energy harvesting in a deregulated environment," Energy, Elsevier, vol. 96(C), pages 614-624.
    14. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2016. "A multi-objective optimization framework for risk-controlled integration of renewable generation into electric power systems," Energy, Elsevier, vol. 106(C), pages 712-727.
    15. 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.

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