IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i11p3346-d570294.html
   My bibliography  Save this article

Optimization of IEDs Position in MV Smart Grids through Integer Linear Programming

Author

Listed:
  • Francesco Bonavolontà

    (Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy
    These authors contributed equally to this work.)

  • Vincenzo Caragallo

    (Operation and Maintenance–Network Analysis and Maintenance, E-Distribuzione S.p.A., 80142 Naples, Italy
    These authors contributed equally to this work.)

  • Alessandro Fatica

    (Operation and Maintenance–Network Analysis and Maintenance, E-Distribuzione S.p.A., 80142 Naples, Italy
    These authors contributed equally to this work.)

  • Annalisa Liccardo

    (Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy
    These authors contributed equally to this work.)

  • Adriano Masone

    (Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy
    These authors contributed equally to this work.)

  • Claudio Sterle

    (Department of Electrical Engineering and Information Technology, University of Naples Federico II, 80125 Naples, Italy
    These authors contributed equally to this work.)

Abstract

In the paper, an analytical method for determining the optimal positioning of intelligent electronic devices in medium voltage grids is proposed. Intelligent electronic devices are automated devices able to communicate one with each other and command the circuit breaker in order to localize and isolate a line fault as fast as possible. However, the number of intelligent electronic devices to install has to be limited, due to the relevant installation costs and the reduction in the transmission bandwidth caused by the increased number of exchanged messages. So, the electrical distributor has to carefully detect the nodes of the grid where the intelligent electronic devices have to be installed. The authors propose a method based on integer linear programming, which, given the number of intelligent electronic devices to install, finds their optimal position, i.e., the one that minimizes the penalties associated with the power down experienced by customers. In order to highlight the offered advantages in terms of computational effort, the proposed approach has been assessed with a real medium voltage grid.

Suggested Citation

  • Francesco Bonavolontà & Vincenzo Caragallo & Alessandro Fatica & Annalisa Liccardo & Adriano Masone & Claudio Sterle, 2021. "Optimization of IEDs Position in MV Smart Grids through Integer Linear Programming," Energies, MDPI, vol. 14(11), pages 1-16, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3346-:d:570294
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/11/3346/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/11/3346/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mladenovic, Nenad & Brimberg, Jack & Hansen, Pierre & Moreno-Perez, Jose A., 2007. "The p-median problem: A survey of metaheuristic approaches," European Journal of Operational Research, Elsevier, vol. 179(3), pages 927-939, June.
    2. Leopoldo Angrisani & Francesco Bonavolontà & Annalisa Liccardo & Rosario Schiano Lo Moriello, 2018. "On the Use of LoRa Technology for Logic Selectivity in MV Distribution Networks," Energies, MDPI, vol. 11(11), pages 1-34, November.
    3. Cristian Cepeda & Cesar Orozco-Henao & Winston Percybrooks & Juan Diego Pulgarín-Rivera & Oscar Danilo Montoya & Walter Gil-González & Juan Carlos Vélez, 2020. "Intelligent Fault Detection System for Microgrids," Energies, MDPI, vol. 13(5), pages 1-21, March.
    4. Davide Della Giustina & Amelia Alvarez de Sotomayor & Alessio Dedè & Francisco Ramos, 2020. "A Model-Based Design of Distributed Automation Systems for the Smart Grid: Implementation and Validation," Energies, MDPI, vol. 13(14), pages 1-19, July.
    5. Soon-Ryul Nam & Woong-Hie Ko & Sopheap Key & Sang-Hee Kang & Nam-Ho Lee, 2021. "IEC 61850-Based Centralized Protection against Single Line-To-Ground Faults in Ungrounded Distribution Systems," Energies, MDPI, vol. 14(3), pages 1-15, January.
    6. Barbaros C. Tansel & Richard L. Francis & Timothy J. Lowe, 1983. "State of the Art---Location on Networks: A Survey. Part I: The p-Center and p-Median Problems," Management Science, INFORMS, vol. 29(4), pages 482-497, April.
    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. Annalisa Liccardo & Francesco Bonavolontà & Ignazio Romano & Rosario Schiano Lo Moriello, 2021. "Optimization and Performance Assessment of a Logic Selectivity Solution Based on LoRa Communication," Energies, MDPI, vol. 14(21), pages 1-17, November.

    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. Annalisa Liccardo & Francesco Bonavolontà & Ignazio Romano & Rosario Schiano Lo Moriello, 2021. "Optimization and Performance Assessment of a Logic Selectivity Solution Based on LoRa Communication," Energies, MDPI, vol. 14(21), pages 1-17, November.
    2. Corinna Heßler & Kaouthar Deghdak, 2017. "Discrete parallel machine makespan ScheLoc problem," Journal of Combinatorial Optimization, Springer, vol. 34(4), pages 1159-1186, November.
    3. Colmenar, J. Manuel & Greistorfer, Peter & Martí, Rafael & Duarte, Abraham, 2016. "Advanced Greedy Randomized Adaptive Search Procedure for the Obnoxious p-Median problem," European Journal of Operational Research, Elsevier, vol. 252(2), pages 432-442.
    4. Dumitru Toader & Maria Vintan & Claudiu Solea & Daniela Vesa & Marian Greconici, 2021. "Analysis of the Possibilities of Selective Detection of a Single Line-to-Ground Fault in a Medium Voltage Network with Isolated Neutral," Energies, MDPI, vol. 14(21), pages 1-19, October.
    5. Fadda, Edoardo & Manerba, Daniele & Cabodi, Gianpiero & Camurati, Paolo Enrico & Tadei, Roberto, 2021. "Comparative analysis of models and performance indicators for optimal service facility location," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    6. Behrooz Alizadeh & Somayeh Bakhteh, 2017. "A modified firefly algorithm for general inverse p-median location problems under different distance norms," OPSEARCH, Springer;Operational Research Society of India, vol. 54(3), pages 618-636, September.
    7. Tao Zhuolin & Zheng Qingjing & Kong Hui, 2018. "A Modified Gravity p-Median Model for Optimizing Facility Locations," Journal of Systems Science and Information, De Gruyter, vol. 6(5), pages 421-434, October.
    8. Rolland, Erik & Schilling, David A. & Current, John R., 1997. "An efficient tabu search procedure for the p-Median Problem," European Journal of Operational Research, Elsevier, vol. 96(2), pages 329-342, January.
    9. Michael Brusco & Douglas Steinley, 2015. "Affinity Propagation and Uncapacitated Facility Location Problems," Journal of Classification, Springer;The Classification Society, vol. 32(3), pages 443-480, October.
    10. Joshua Q. Hale & Enlu Zhou & Jiming Peng, 2017. "A Lagrangian search method for the P-median problem," Journal of Global Optimization, Springer, vol. 69(1), pages 137-156, September.
    11. Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    12. Campos Rodrí­guez, Clara M. & Moreno Pérez, José A., 2008. "Multiple voting location problems," European Journal of Operational Research, Elsevier, vol. 191(2), pages 437-453, December.
    13. Hernandez-Matheus, Alejandro & Löschenbrand, Markus & Berg, Kjersti & Fuchs, Ida & Aragüés-Peñalba, Mònica & Bullich-Massagué, Eduard & Sumper, Andreas, 2022. "A systematic review of machine learning techniques related to local energy communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    14. Snežana Tadić & Mladen Krstić & Željko Stević & Miloš Veljović, 2023. "Locating Collection and Delivery Points Using the p -Median Location Problem," Logistics, MDPI, vol. 7(1), pages 1-17, February.
    15. Zhen, Lu & Gao, Jiajing & Tan, Zheyi & Laporte, Gilbert & Baldacci, Roberto, 2023. "Territorial design for customers with demand frequency," European Journal of Operational Research, Elsevier, vol. 309(1), pages 82-101.
    16. Pablo Adasme & Ali Dehghan Firoozabadi, 2019. "Facility Location with Tree Topology and Radial Distance Constraints," Complexity, Hindawi, vol. 2019, pages 1-29, November.
    17. Ehsan Ahmadi & Dale T. Masel & Seth Hostetler, 2023. "A Data-Driven Decision-Making Model for Configuring Surgical Trays Based on the Likelihood of Instrument Usages," Mathematics, MDPI, vol. 11(9), pages 1-26, May.
    18. Stracqualursi, Erika & Rosato, Antonello & Di Lorenzo, Gianfranco & Panella, Massimo & Araneo, Rodolfo, 2023. "Systematic review of energy theft practices and autonomous detection through artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
    19. Vladimir Marianov & Daniel Serra, 2009. "Median problems in networks," Economics Working Papers 1151, Department of Economics and Business, Universitat Pompeu Fabra.
    20. Faisal Mumtaz & Haseeb Hassan Khan & Amad Zafar & Muhammad Umair Ali & Kashif Imran, 2022. "A State-Observer-Based Protection Scheme for AC Microgrids with Recurrent Neural Network Assistance," Energies, MDPI, vol. 15(22), pages 1-22, November.

    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:14:y:2021:i:11:p:3346-:d:570294. 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.