IDEAS home Printed from https://ideas.repec.org/a/spr/joheur/v26y2020i1d10.1007_s10732-019-09421-0.html
   My bibliography  Save this article

MIQP model and improvement heuristic for power loss minimization in distribution system with network reconfiguration

Author

Listed:
  • Karla B. Freitas

    (University of São Paulo)

  • Márcio S. Arantes

    (Senai Innovation Institute for Embedded Systems)

  • Claudio F. M. Toledo

    (University of São Paulo)

  • Alexandre C. B. Delbem

    (University of São Paulo)

Abstract

The problem of reconfiguration in electrical power distribution systems deals with changes in the network topology using maneuvers switches. This is an optimization problem where one of the goals is to minimize losses following constraints such as faults isolation, load feeders balancing and voltage profile improvement. The present paper solves such problem by introducing a mixed-integer quadratic program (MIQP) model, which aims to return optimal configurations. An improvement heuristic, based on the solution of MIQP sub models, is also introduced. The MIQP model and improvement heuristic are validated over eight benchmark power systems, and the results achieved are compared against those recently reported by literature. A new set of 10 large sized bus-systems is also defined as replication of a benchmark bus system from literature. The computational results show that our MIQP model and heuristic are able to find optimal configurations for those benchmark systems, as well as to provide good quality solution for the large sized bus-systems within a reduced computational time.

Suggested Citation

  • Karla B. Freitas & Márcio S. Arantes & Claudio F. M. Toledo & Alexandre C. B. Delbem, 2020. "MIQP model and improvement heuristic for power loss minimization in distribution system with network reconfiguration," Journal of Heuristics, Springer, vol. 26(1), pages 59-81, February.
    • Handle: RePEc:spr:joheur:v:26:y:2020:i:1:d:10.1007_s10732-019-09421-0
    DOI: 10.1007/s10732-019-09421-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10732-019-09421-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10732-019-09421-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. H. Faria & M. G. C. Resende & D. Ernst, 2017. "A biased random key genetic algorithm applied to the electric distribution network reconfiguration problem," Journal of Heuristics, Springer, vol. 23(6), pages 533-550, December.
    2. Avella, Pasquale & Villacci, Domenico & Sforza, Antonio, 2005. "A Steiner arborescence model for the feeder reconfiguration in electric distribution networks," European Journal of Operational Research, Elsevier, vol. 164(2), pages 505-509, July.
    3. Helber, Stefan & Sahling, Florian, 2010. "A fix-and-optimize approach for the multi-level capacitated lot sizing problem," International Journal of Production Economics, Elsevier, vol. 123(2), pages 247-256, February.
    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. K. Prakash & F. R. Islam & K. A. Mamun & H. R. Pota, 2020. "Configurations of Aromatic Networks for Power Distribution System," Sustainability, MDPI, vol. 12(10), pages 1-17, May.

    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. Charles, Mehdi & Dauzère-Pérès, Stéphane & Kedad-Sidhoum, Safia & Mazhoud, Issam, 2022. "Motivations and analysis of the capacitated lot-sizing problem with setup times and minimum and maximum ending inventories," European Journal of Operational Research, Elsevier, vol. 302(1), pages 203-220.
    2. Sereshti, Narges & Adulyasak, Yossiri & Jans, Raf, 2024. "Managing flexibility in stochastic multi-level lot sizing problem with service level constraints," Omega, Elsevier, vol. 122(C).
    3. Rossi, André & Aubry, Alexis & Jacomino, Mireille, 2012. "Connectivity-and-hop-constrained design of electricity distribution networks," European Journal of Operational Research, Elsevier, vol. 218(1), pages 48-57.
    4. Junqueira, Rogerio de Ávila Ribeiro & Morabito, Reinaldo, 2019. "Modeling and solving a sugarcane harvest front scheduling problem," International Journal of Production Economics, Elsevier, vol. 213(C), pages 150-160.
    5. Lang, Jan Christian & Shen, Zuo-Jun Max, 2011. "Fix-and-optimize heuristics for capacitated lot-sizing with sequence-dependent setups and substitutions," European Journal of Operational Research, Elsevier, vol. 214(3), pages 595-605, November.
    6. Alireza Etminaniesfahani & Hanyu Gu & Leila Moslemi Naeni & Amir Salehipour, 2024. "An efficient relax-and-solve method for the multi-mode resource constrained project scheduling problem," Annals of Operations Research, Springer, vol. 338(1), pages 41-68, July.
    7. Alexander Franz & Julia Rieck & Jürgen Zimmermann, 2019. "Fix-and-optimize procedures for solving the long-term unit commitment problem with pumped storages," Annals of Operations Research, Springer, vol. 274(1), pages 241-265, March.
    8. Xia, Liang & Chan, Ming-yin & Qu, Minglu & Xu, Xiangguo & Deng, Shiming, 2011. "A fundamental study on the optimal/near-optimal shape of a network for energy distribution," Energy, Elsevier, vol. 36(11), pages 6471-6478.
    9. Thevenin, Simon & Ben-Ammar, Oussama & Brahimi, Nadjib, 2022. "Robust optimization approaches for purchase planning with supplier selection under lead time uncertainty," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1199-1215.
    10. Wei, Wenchao & Guimarães, Luis & Amorim, Pedro & Almada-Lobo, Bernardo, 2017. "Tactical production and distribution planning with dependency issues on the production process," Omega, Elsevier, vol. 67(C), pages 99-114.
    11. Zamani Dadaneh, Dariush & Moradi, Sajad & Alizadeh, Behrooz, 2023. "Simultaneous planning of purchase orders, production, and inventory management under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 265(C).
    12. Yilmaz, Dogacan & Büyüktahtakın, İ. Esra, 2024. "An expandable machine learning-optimization framework to sequential decision-making," European Journal of Operational Research, Elsevier, vol. 314(1), pages 280-296.
    13. Neves-Moreira, F. & Amorim, P. & Guimarães, L. & Almada-Lobo, B., 2016. "A long-haul freight transportation problem: Synchronizing resources to deliver requests passing through multiple transshipment locations," European Journal of Operational Research, Elsevier, vol. 248(2), pages 487-506.
    14. Ameling, Justus & Gust, Gunther, 2024. "Automated feeder routing for underground electricity distribution networks based on aerial images," European Journal of Operational Research, Elsevier, vol. 318(2), pages 629-641.
    15. Taillard, Éric D. & Helsgaun, Keld, 2019. "POPMUSIC for the travelling salesman problem," European Journal of Operational Research, Elsevier, vol. 272(2), pages 420-429.
    16. Gust, Gunther & Schlüter, Alexander & Feuerriegel, Stefan & Úbeda, Ignacio & Lee, Jonathan T. & Neumann, Dirk, 2024. "Designing electricity distribution networks: The impact of demand coincidence," European Journal of Operational Research, Elsevier, vol. 315(1), pages 271-288.
    17. Cunha, Jesus O. & Melo, Rafael A., 2021. "Valid inequalities, preprocessing, and an effective heuristic for the uncapacitated three-level lot-sizing and replenishment problem with a distribution structure," European Journal of Operational Research, Elsevier, vol. 295(3), pages 874-892.
    18. Stefan Helber & Daniel Böhme & Farid Oucherif & Svenja Lagershausen & Steffen Kasper, 2016. "A hierarchical facility layout planning approach for large and complex hospitals," Flexible Services and Manufacturing Journal, Springer, vol. 28(1), pages 5-29, June.
    19. Vizcaino González, José Federico & Lyra, Christiano & Usberti, Fábio Luiz, 2012. "A pseudo-polynomial algorithm for optimal capacitor placement on electric power distribution networks," European Journal of Operational Research, Elsevier, vol. 222(1), pages 149-156.
    20. Franco Basso & Juan Pablo Contreras & Raúl Pezoa & Alejandro Troncozo & Mauricio Varas, 2023. "Optimizing the wine transportation process from bottling plants to ports," Operational Research, Springer, vol. 23(2), pages 1-28, June.

    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:spr:joheur:v:26:y:2020:i:1:d:10.1007_s10732-019-09421-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.