IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i5p1686-d757390.html
   My bibliography  Save this article

Distribution Network Reconfiguration Considering Voltage and Current Unbalance Indexes and Variable Demand Solved through a Selective Bio-Inspired Metaheuristic

Author

Listed:
  • Cassio Gerez

    (Polytechnic School, University of São Paulo—EPUSP, São Paulo 05508-010, SP, Brazil
    Current address: Electrical Engineering Department, University of São Paulo, Prof. Luciano Gualberto Avenue, Lane 3, 158–Butantã, São Paulo 05508-010, SP, Brazil.
    These authors contributed equally to this work.)

  • Eduardo Coelho Marques Costa

    (Polytechnic School, University of São Paulo—EPUSP, São Paulo 05508-010, SP, Brazil
    These authors contributed equally to this work.)

  • Alfeu J. Sguarezi Filho

    (Center for Engineering, Modeling and Applied Social Sciences (CECS), Federal University of ABC—UFABC, Santo Andre 09210-580, SP, Brazil)

Abstract

Operation of distribution networks involves a series of criteria that should be met, aiming for the correct and optimal behavior of such systems. Some of the major drawbacks found when studying these networks is the real losses related to them. To overcome this problem, distribution network reconfiguration (DNR) is an efficient tool due to the low costs involved in its implementation. The majority of studies regarding this subject treat the problem by considering networks only as three-phase balanced, modeled as single-phase grids with fixed power demand, which is far from representing the characteristics of real networks (e.g., unbalanced loads, variable power and unbalance indexes). Due to the combinatorial nature of the problem, metaheuristic techniques are powerful tools for the inclusion of such characteristics. In this sense, this paper proposes a study of DNR considering balanced and unbalanced systems with variable power demand. An analysis of the direct influence of voltage unbalance index (VUI) and current unbalance index (CUI) is carried out for unbalanced cases. To solve the DNR problem, a selective bio-inspired metaheuristic based on micro bats’ behavior named the selective bat algorithm (SBAT) is used together with the EPRI-OpenDSS software (California, US, EPRI). Tests are initially conducted on balanced systems, aiming to validate the technique proposed for both demands and state their differences, and then they are conducted on unbalanced systems to study the influence of VUI and CUI in the DNR solution.

Suggested Citation

  • Cassio Gerez & Eduardo Coelho Marques Costa & Alfeu J. Sguarezi Filho, 2022. "Distribution Network Reconfiguration Considering Voltage and Current Unbalance Indexes and Variable Demand Solved through a Selective Bio-Inspired Metaheuristic," Energies, MDPI, vol. 15(5), pages 1-27, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1686-:d:757390
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/5/1686/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/5/1686/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mohamed Abd-El-Hakeem Mohamed & Ziad M. Ali & Mahrous Ahmed & Saad F. Al-Gahtani, 2021. "Energy Saving Maximization of Balanced and Unbalanced Distribution Power Systems via Network Reconfiguration and Optimum Capacitor Allocation Using a Hybrid Metaheuristic Algorithm," Energies, MDPI, vol. 14(11), pages 1-24, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abdulaziz Alanazi & Mohana Alanazi, 2022. "Artificial Electric Field Algorithm-Pattern Search for Many-Criteria Networks Reconfiguration Considering Power Quality and Energy Not Supplied," Energies, MDPI, vol. 15(14), pages 1-27, July.
    2. 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.
    3. Raida Sellami & Imene Khenissi & Tawfik Guesmi & Badr M. Alshammari & Khalid Alqunun & Ahmed S. Alshammari & Kamel Tlijani & Rafik Neji, 2022. "Optimal Reconfiguration of Distribution Network Considering Stochastic Wind Energy and Load Variation Using Hybrid SAMPSO Optimization Method," Sustainability, MDPI, vol. 14(18), pages 1-25, September.
    4. Zifa Liu & Jieyu Li & Yunyang Liu & Puyang Yu & Junteng Shao, 2022. "Collaborative Optimized Operation Model of Multi-Character Distribution Network Considering Multiple Uncertain Factors and Demand Response," Energies, MDPI, vol. 15(12), pages 1-19, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nicholas D. de Andrade & Ruben B. Godoy & Edson A. Batista & Moacyr A. G. de Brito & Rafael L. R. Soares, 2022. "Embedded FPGA Controllers for Current Compensation Based on Modern Power Theories," Energies, MDPI, vol. 15(17), pages 1-17, August.
    2. Minsheng Yang & Jianqi Li & Rui Du & Jianying Li & Jian Sun & Xiaofang Yuan & Jiazhu Xu & Shifu Huang, 2022. "Reactive Power Optimization Model for Distribution Networks Based on the Second-Order Cone and Interval Optimization," Energies, MDPI, vol. 15(6), pages 1-16, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1686-:d:757390. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.