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An aggregated model for coordinated planning and reconfiguration of electric distribution networks

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  • Arasteh, Hamidreza
  • Sepasian, Mohammad Sadegh
  • Vahidinasab, Vahid

Abstract

This paper proposes a coordinated distribution system reconfiguration and planning model to deal with the problem of active distribution expansion planning. DR (Demand response) programs are modeled as virtual distributed resources to cover the effect of uncertain parameters. A bi-level optimization procedure is developed to solve the proposed model. At the first level, an optimization problem is solved using PSO (particle swarm optimization) algorithm to determine the system expansion and reconfiguration plans. Next, the second level minimization problem is developed based on the sensitivity analysis. The DR programs are taken into account in the second level problem to encounter with the problem uncertainties. Therefore, the proposed model incorporates the problem of DSR (distribution system reconfiguration) with system expansion problem, while the presence of DR is considered to enhance the effectiveness of the problem. The IEEE 33-bus standard test system is utilized to investigate the performance of the proposed model. The simulation results approve the advantages of the proposed model and its economical profits for distribution network owners.

Suggested Citation

  • Arasteh, Hamidreza & Sepasian, Mohammad Sadegh & Vahidinasab, Vahid, 2016. "An aggregated model for coordinated planning and reconfiguration of electric distribution networks," Energy, Elsevier, vol. 94(C), pages 786-798.
    • Handle: RePEc:eee:energy:v:94:y:2016:i:c:p:786-798
    DOI: 10.1016/j.energy.2015.11.053
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    2. 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).
    3. Syed Ali Abbas Kazmi & Muhammad Khuram Shahzad & Dong Ryeol Shin, 2017. "Multi-Objective Planning Techniques in Distribution Networks: A Composite Review," Energies, MDPI, vol. 10(2), pages 1-44, February.
    4. Azizivahed, Ali & Narimani, Hossein & Fathi, Mehdi & Naderi, Ehsan & Safarpour, Hamid Reza & Narimani, Mohammad Rasoul, 2018. "Multi-objective dynamic distribution feeder reconfiguration in automated distribution systems," Energy, Elsevier, vol. 147(C), pages 896-914.
    5. Monadi, Mehdi & Zamani, M. Amin & Koch-Ciobotaru, Cosmin & Candela, Jose Ignacio & Rodriguez, Pedro, 2016. "A communication-assisted protection scheme for direct-current distribution networks," Energy, Elsevier, vol. 109(C), pages 578-591.
    6. Zixiao Ban & Fei Teng & Huifeng Zhang & Shuo Li & Geyang Xiao & Yajuan Guan, 2023. "Distributed Fixed-Time Energy Management for Port Microgrid Considering Transmissive Efficiency," Mathematics, MDPI, vol. 11(17), pages 1-13, August.
    7. Kavousi-Fard, Abdollah & Khodaei, Amin, 2016. "Efficient integration of plug-in electric vehicles via reconfigurable microgrids," Energy, Elsevier, vol. 111(C), pages 653-663.
    8. Liu, Yuan & He, Li & Shen, Jing, 2017. "Optimization-based provincial hybrid renewable and non-renewable energy planning – A case study of Shanxi, China," Energy, Elsevier, vol. 128(C), pages 839-856.
    9. Moradijoz, M. & Moghaddam, M. Parsa & Haghifam, M.R., 2018. "A flexible active distribution system expansion planning model: A risk-based approach," Energy, Elsevier, vol. 145(C), pages 442-457.

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