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A New Method for Distribution Network Reconfiguration Analysis under Different Load Demands

Author

Listed:
  • Firas M. F. Flaih

    (School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    General Directorate of North Distribution Electricity, Ministry of Electricity, 10013 Baghdad, Iraq)

  • Xiangning Lin

    (School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Mohammed Kdair Abd

    (School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    Department of Electrical Engineering, University of Technology, Ministry of Higher Education and Scientific Research, 10066 Baghdad, Iraq)

  • Samir M. Dawoud

    (School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
    Department of Electrical Power Engineering, Tanta University, 31527 Tanta, Egypt)

  • Zhengtian Li

    (School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Owolabi Sunday Adio

    (School of Electrical and Electronics Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

The strategies of distribution network reconfiguration are applicable for minimizing power loss and saving electrical energy in the distribution system. Network reconfiguration is usually represented by constant load demand so ignoring the variability of load demand causes uncertainty and misleading results in the minimization of power loss. This paper consists of two parts: first, the reconfiguration was accomplished using an optimization framework based on constant load to find sets of optimal switches. The minimization of active power loss was taken as an objective function while bus voltage, branch current and system radiality were taken as system constraints. The study was applied to a 33-bus test distribution network, which is exceedingly used as test examples for solving reconfiguration problems. Second, lists of the configurations set obtained from the first part, as well as other different optimization methods proposed earlier under constant load demand were taken as test switches. Additionally, the network in the presence of distributed generators was taken to analyze the reconfiguration under an active network. Two types of load demands; the variable load and voltage-dependent load, are proposed to represent the practical load demands. This paper presents a new method for good analysis as it defines the effect of loading levels and loading patterns on a distribution system performance for passive and active networks. The proposed approach tries to find the actual power loss under different characteristics of loads. Therefore, the probable benefit of this approach is the contribution to providing more flexibility for electrical utilities in terms of distribution system operation, while also opening new prospects in the automation of smart distribution systems.

Suggested Citation

  • Firas M. F. Flaih & Xiangning Lin & Mohammed Kdair Abd & Samir M. Dawoud & Zhengtian Li & Owolabi Sunday Adio, 2017. "A New Method for Distribution Network Reconfiguration Analysis under Different Load Demands," Energies, MDPI, vol. 10(4), pages 1-19, April.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:455-:d:94715
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    References listed on IDEAS

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    1. Kalambe, Shilpa & Agnihotri, Ganga, 2014. "Loss minimization techniques used in distribution network: bibliographical survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 29(C), pages 184-200.
    2. Bogdan Tomoiagă & Mircea Chindriş & Andreas Sumper & Antoni Sudria-Andreu & Roberto Villafafila-Robles, 2013. "Pareto Optimal Reconfiguration of Power Distribution Systems Using a Genetic Algorithm Based on NSGA-II," Energies, MDPI, vol. 6(3), pages 1-17, March.
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    Cited by:

    1. Pengwei Cong & Wei Tang & Lu Zhang & Bo Zhang & Yongxiang Cai, 2017. "Day-Ahead Active Power Scheduling in Active Distribution Network Considering Renewable Energy Generation Forecast Errors," Energies, MDPI, vol. 10(9), pages 1-20, August.
    2. Mohd Ikhwan Muhammad Ridzuan & Sasa Z. Djokic, 2019. "Energy Regulator Supply Restoration Time," Energies, MDPI, vol. 12(6), pages 1-16, March.
    3. Hun-Chul Seo, 2017. "New Adaptive Reclosing Technique in Unbalanced Distribution System," Energies, MDPI, vol. 10(7), pages 1-16, July.
    4. Rade Čađenović & Damir Jakus & Petar Sarajčev & Josip Vasilj, 2018. "Optimal Distribution Network Reconfiguration through Integration of Cycle-Break and Genetic Algorithms," Energies, MDPI, vol. 11(5), pages 1-19, May.

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