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A Mixed-Integer Nonlinear Programming Model for Optimal Reconfiguration of DC Distribution Feeders

Author

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  • O. D. Montoya

    (Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá D.C. 11021, Colombia
    Laboratorio Inteligente de Energía, Universidad Tecnológica de Bolívar, Cartagena 131001, Colombia)

  • W. Gil-González

    (Grupo GIIEN, Facultad de Ingeniería, Institución Universitaria Pascual Bravo, Campus Robledo, Medellín 050036, Colombia)

  • J. C. Hernández

    (Department of Electrical Engineering, University of Jaén, Campus Lagunillas s/n, Edificio A3, 23071 Jaén, Spain)

  • D. A. Giral-Ramírez

    (Facultad Tecnológica, Universidad Distrital Francisco José de Caldas, Bogotá D.C. 11021, Colombia)

  • A. Medina-Quesada

    (Department of Electrical Engineering, University of Jaén, Campus Lagunillas s/n, Edificio A3, 23071 Jaén, Spain)

Abstract

This paper deals with the optimal reconfiguration problem of DC distribution networks by proposing a new mixed-integer nonlinear programming (MINLP) formulation. This MINLP model focuses on minimising the power losses in the distribution lines by reformulating the classical power balance equations through a branch-to-node incidence matrix. The general algebraic modelling system (GAMS) is chosen as a solution tool, showing in tutorial form the implementation of the proposed MINLP model in a 6-nodes test feeder with 10 candidate lines. The validation of the MINLP formulation is performed in two classical 10-nodes DC test feeders. These are typically used for power flow and optimal power flow analyses. Numerical results demonstrate that power losses are reduced by about 16 % when the optimal reconfiguration plan is found. The numerical validations are made in the GAMS software licensed by Universidad Tecnológica de Bolívar.

Suggested Citation

  • O. D. Montoya & W. Gil-González & J. C. Hernández & D. A. Giral-Ramírez & A. Medina-Quesada, 2020. "A Mixed-Integer Nonlinear Programming Model for Optimal Reconfiguration of DC Distribution Feeders," Energies, MDPI, vol. 13(17), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4440-:d:405065
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    References listed on IDEAS

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    1. Walter Gil-González & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña & Fernando Cruz-Peragón & Gerardo Alcalá, 2020. "Economic Dispatch of Renewable Generators and BESS in DC Microgrids Using Second-Order Cone Optimization," Energies, MDPI, vol. 13(7), pages 1-15, April.
    2. Shimin Xue & Chaochao Chen & Yi Jin & Yongli Li & Botong Li & Ying Wang, 2014. "Protection for DC Distribution System with Distributed Generator," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-12, June.
    3. Tung Tran The & Dieu Vo Ngoc & Nguyen Tran Anh, 2020. "Distribution Network Reconfiguration for Power Loss Reduction and Voltage Profile Improvement Using Chaotic Stochastic Fractal Search Algorithm," Complexity, Hindawi, vol. 2020, pages 1-15, March.
    4. Ben Hamida, Imen & Salah, Saoussen Brini & Msahli, Faouzi & Mimouni, Mohamed Faouzi, 2018. "Optimal network reconfiguration and renewable DG integration considering time sequence variation in load and DGs," Renewable Energy, Elsevier, vol. 121(C), pages 66-80.
    5. Naghiloo, Ahmad & Abbaspour, Majid & Mohammadi-Ivatloo, Behnam & Bakhtari, Khosro, 2015. "GAMS based approach for optimal design and sizing of a pressure retarded osmosis power plant in Bahmanshir river of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1559-1565.
    6. Tao Shen & Yanjun Li & Ji Xiang, 2018. "A Graph-Based Power Flow Method for Balanced Distribution Systems," Energies, MDPI, vol. 11(3), pages 1-11, February.
    7. Fatma Yaprakdal & Mustafa Baysal & Amjad Anvari-Moghaddam, 2019. "Optimal Operational Scheduling of Reconfigurable Microgrids in Presence of Renewable Energy Sources," Energies, MDPI, vol. 12(10), pages 1-17, May.
    8. Oscar Danilo Montoya & Walter Gil-González & Edwin Rivas-Trujillo, 2020. "Optimal Location-Reallocation of Battery Energy Storage Systems in DC Microgrids," Energies, MDPI, vol. 13(9), pages 1-20, May.
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