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Application of multi-objective optimization algorithm for siting and sizing of distributed generations in distribution networks

Author

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  • J. Rajalakshmi

    (Fatima Michael College of Engineering and Technology)

  • S. Durairaj

    (Dhanalakshmi Srinivasan Engineering College)

Abstract

Multi-objective optimization for siting and sizing of Distributed Generations (DGs) is difficult because of the highly non-linear interactions of a large number of variables. Furthermore, effective optimization algorithms are often highly problem-dependent and need broad tuning, which limits their applicability to the real world. To address this issue, in this study, Multi-Objective Differential Evolution (MODE) algorithms have been proposed for siting and sizing of DGs. The site and size of DGs play a vital role in the minimization of real power losses and enhancement of voltage profile in distribution systems. This study intends to attain the technical, economic, and environmental benefits of DGs. Hence, the Objective Functions such as minimization of power losses, voltage deviation, energy cost, emissions while generating power, and enhancement of the Voltage Stability Index have been considered. The simulations of two different multi-objective operational cases have been carried out on IEEE 33 bus system, IEEE 69 bus system, and Tamil Nadu Generation and Distribution Corporation Limited, as a real part of 62 bus Indian Utility System. The simulation results of MODE have shown its superior performance and have ensured the economic and environmental benefits of integrating DGs.

Suggested Citation

  • J. Rajalakshmi & S. Durairaj, 2021. "Application of multi-objective optimization algorithm for siting and sizing of distributed generations in distribution networks," Journal of Combinatorial Optimization, Springer, vol. 41(2), pages 267-289, February.
    • Handle: RePEc:spr:jcomop:v:41:y:2021:i:2:d:10.1007_s10878-020-00681-2
    DOI: 10.1007/s10878-020-00681-2
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    References listed on IDEAS

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    1. Pesaran H.A., Mahmoud & Nazari-Heris, Morteza & Mohammadi-Ivatloo, Behnam & Seyedi, Heresh, 2020. "A hybrid genetic particle swarm optimization for distributed generation allocation in power distribution networks," Energy, Elsevier, vol. 209(C).
    2. Viral, Rajkumar & Khatod, D.K., 2012. "Optimal planning of distributed generation systems in distribution system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 5146-5165.
    3. Das, Sangeeta & Das, Debapriya & Patra, Amit, 2019. "Operation of distribution network with optimal placement and sizing of dispatchable DGs and shunt capacitors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    4. Doagou-Mojarrad, Hasan & Gharehpetian, G.B. & Rastegar, H. & Olamaei, Javad, 2013. "Optimal placement and sizing of DG (distributed generation) units in distribution networks by novel hybrid evolutionary algorithm," Energy, Elsevier, vol. 54(C), pages 129-138.
    5. Gitizadeh, Mohsen & Vahed, Ali Azizi & Aghaei, Jamshid, 2013. "Multistage distribution system expansion planning considering distributed generation using hybrid evolutionary algorithms," Applied Energy, Elsevier, vol. 101(C), pages 655-666.
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    Cited by:

    1. Chandrasekaran Venkatesan & Raju Kannadasan & Mohammed H. Alsharif & Mun-Kyeom Kim & Jamel Nebhen, 2021. "A Novel Multiobjective Hybrid Technique for Siting and Sizing of Distributed Generation and Capacitor Banks in Radial Distribution Systems," Sustainability, MDPI, vol. 13(6), pages 1-34, March.

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