IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i17p6332-d1230220.html
   My bibliography  Save this article

A Survey of Time-Series Prediction for Digitally Enabled Maintenance of Electrical Grids

Author

Listed:
  • Hamid Mirshekali

    (SDU Center for Energy Informatics, University of Southern Denmark, 5230 Odense, Denmark)

  • Athila Q. Santos

    (SDU Center for Energy Informatics, University of Southern Denmark, 5230 Odense, Denmark)

  • Hamid Reza Shaker

    (SDU Center for Energy Informatics, University of Southern Denmark, 5230 Odense, Denmark)

Abstract

The maintenance of electrical grids is crucial for improving their reliability, performance, and cost-effectiveness. It involves employing various strategies to ensure smooth operation and address potential issues. With the advancement of digital technologies, utilizing time-series prediction has emerged as a valuable approach to enhance maintenance practices in electrical systems. The utilization of various recorded data from electrical grid components plays a crucial role in digitally enabled maintenance. However, the comprehensive exploration of time-series data prediction for maintenance is still lacking. This review paper extensively explores different time series that can be utilized to support maintenance efforts in electrical grids with regard to different maintenance strategies and grid components. The digitization of the electrical grids has enabled the collection of diverse time-series data from various network components. In this context, the paper provides an overview of how these time-series and historical-fault data can be utilized for maintenance purposes in electrical grids. Various maintenance levels and time series used for maintenance purposes in different components of the electrical grid are presented.

Suggested Citation

  • Hamid Mirshekali & Athila Q. Santos & Hamid Reza Shaker, 2023. "A Survey of Time-Series Prediction for Digitally Enabled Maintenance of Electrical Grids," Energies, MDPI, vol. 16(17), pages 1-29, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6332-:d:1230220
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/17/6332/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/17/6332/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Wuest, Thorsten & Stahre, Johan, 2020. "Smart Maintenance: a research agenda for industrial maintenance management," International Journal of Production Economics, Elsevier, vol. 224(C).
    2. Bobbio, A. & Bonanni, G. & Ciancamerla, E. & Clemente, R. & Iacomini, A. & Minichino, M. & Scarlatti, A. & Terruggia, R. & Zendri, E., 2010. "Unavailability of critical SCADA communication links interconnecting a power grid and a Telco network," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1345-1357.
    3. Adriana Mar & Pedro Pereira & João F. Martins, 2019. "A Survey on Power Grid Faults and Their Origins: A Contribution to Improving Power Grid Resilience," Energies, MDPI, vol. 12(24), pages 1-21, December.
    4. Shokrzadeh, Shahab & Ribberink, Hajo & Rishmawi, Issa & Entchev, Evgueniy, 2017. "A simplified control algorithm for utilities to utilize plug-in electric vehicles to reduce distribution transformer overloading," Energy, Elsevier, vol. 133(C), pages 1121-1131.
    5. Moamin A. Mahmoud & Naziffa Raha Md Nasir & Mathuri Gurunathan & Preveena Raj & Salama A. Mostafa, 2021. "The Current State of the Art in Research on Predictive Maintenance in Smart Grid Distribution Network: Fault’s Types, Causes, and Prediction Methods—A Systematic Review," Energies, MDPI, vol. 14(16), pages 1-27, August.
    6. Phylicia Cicilio & David Glennon & Adam Mate & Arthur Barnes & Vishvas Chalishazar & Eduardo Cotilla-Sanchez & Bjorn Vaagensmith & Jake Gentle & Craig Rieger & Richard Wies & Mohammad Heidari Kapourch, 2021. "Resilience in an Evolving Electrical Grid," Energies, MDPI, vol. 14(3), pages 1-25, January.
    7. Enrique Personal & Antonio García & Antonio Parejo & Diego Francisco Larios & Félix Biscarri & Carlos León, 2016. "A Comparison of Impedance-Based Fault Location Methods for Power Underground Distribution Systems," Energies, MDPI, vol. 9(12), pages 1-30, December.
    8. Reddy, S. Surender, 2017. "Optimal scheduling of thermal-wind-solar power system with storage," Renewable Energy, Elsevier, vol. 101(C), pages 1357-1368.
    9. de Faria, Haroldo & Costa, João Gabriel Spir & Olivas, Jose Luis Mejia, 2015. "A review of monitoring methods for predictive maintenance of electric power transformers based on dissolved gas analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 201-209.
    10. Mortensen, Lasse Kappel & Shaker, Hamid Reza & Veje, Christian T., 2022. "Relative fault vulnerability prediction for energy distribution networks," Applied Energy, Elsevier, vol. 322(C).
    11. Muller, Alexandre & Crespo Marquez, Adolfo & Iung, Benoît, 2008. "On the concept of e-maintenance: Review and current research," Reliability Engineering and System Safety, Elsevier, vol. 93(8), pages 1165-1187.
    12. Harriet Fox & Ajit C. Pillai & Daniel Friedrich & Maurizio Collu & Tariq Dawood & Lars Johanning, 2022. "A Review of Predictive and Prescriptive Offshore Wind Farm Operation and Maintenance," Energies, MDPI, vol. 15(2), pages 1-27, January.
    13. Doucoure, Boubacar & Agbossou, Kodjo & Cardenas, Alben, 2016. "Time series prediction using artificial wavelet neural network and multi-resolution analysis: Application to wind speed data," Renewable Energy, Elsevier, vol. 92(C), pages 202-211.
    14. Abdul Rahman, Fariz & Varuttamaseni, Athi & Kintner-Meyer, Michael & Lee, John C., 2013. "Application of fault tree analysis for customer reliability assessment of a distribution power system," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 76-85.
    15. Hamid Mirshekali & Rahman Dashti & Karsten Handrup & Hamid Reza Shaker, 2021. "Real Fault Location in a Distribution Network Using Smart Feeder Meter Data," Energies, MDPI, vol. 14(11), pages 1-16, June.
    Full references (including those not matched with items on IDEAS)

    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. Jorge De La Cruz & Eduardo Gómez-Luna & Majid Ali & Juan C. Vasquez & Josep M. Guerrero, 2023. "Fault Location for Distribution Smart Grids: Literature Overview, Challenges, Solutions, and Future Trends," Energies, MDPI, vol. 16(5), pages 1-37, February.
    2. García, Irene & Huo, Stella & Prado, Raquel & Bravo, Lelys, 2020. "Dynamic Bayesian temporal modeling and forecasting of short-term wind measurements," Renewable Energy, Elsevier, vol. 161(C), pages 55-64.
    3. Peters, Lennart & Madlener, Reinhard, 2017. "Economic evaluation of maintenance strategies for ground-mounted solar photovoltaic plants," Applied Energy, Elsevier, vol. 199(C), pages 264-280.
    4. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Stahre, Johan, 2017. "Maintenance in digitalised manufacturing: Delphi-based scenarios for 2030," International Journal of Production Economics, Elsevier, vol. 191(C), pages 154-169.
    5. Liu, Xiaolei & Lin, Zi & Feng, Ziming, 2021. "Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM," Energy, Elsevier, vol. 227(C).
    6. Genge, Béla & Siaterlis, Christos, 2013. "Analysis of the effects of distributed denial-of-service attacks on MPLS networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 6(2), pages 87-95.
    7. Zhai, Chengwei & Chen, Thomas Ying-jeh & White, Anna Grace & Guikema, Seth David, 2021. "Power outage prediction for natural hazards using synthetic power distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    8. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    9. Mojtaba Qolipour & Ali Mostafaeipour & Mohammad Saidi-Mehrabad & Hamid R Arabnia, 2019. "Prediction of wind speed using a new Grey-extreme learning machine hybrid algorithm: A case study," Energy & Environment, , vol. 30(1), pages 44-62, February.
    10. Muhammad Waseem & Muhammad Adnan Khan & Arman Goudarzi & Shah Fahad & Intisar Ali Sajjad & Pierluigi Siano, 2023. "Incorporation of Blockchain Technology for Different Smart Grid Applications: Architecture, Prospects, and Challenges," Energies, MDPI, vol. 16(2), pages 1-29, January.
    11. Aruna Kanagaraj & Kumudini Devi Raguru Pandu, 2020. "Investigations of Various Market Models in a Deregulated Power Environment Using ACOPF," Energies, MDPI, vol. 13(9), pages 1-17, May.
    12. Sakthivel, V.P. & Thirumal, K. & Sathya, P.D., 2022. "Short term scheduling of hydrothermal power systems with photovoltaic and pumped storage plants using quasi-oppositional turbulent water flow optimization," Renewable Energy, Elsevier, vol. 191(C), pages 459-492.
    13. Andréia S. Santos & Lucas Teles Faria & Mara Lúcia M. Lopes & Carlos R. Minussi, 2023. "Power Distribution Systems’ Vulnerability by Regions Caused by Electrical Discharges," Energies, MDPI, vol. 16(23), pages 1-19, November.
    14. Max Gabriel Steiner & Anderson Diogo Spacek & João Mota Neto & Pedro Rodrigo Silva Moura & Oswaldo Hideo Ando Junior & Cleber Lourenço Izidoro & Luciano Dagostin Bilessimo & Jefferson Diogo Spacek, 2020. "“In Situ” Evaluation of Mechanical Wear of Mobile Contacts of Electricity Voltage Regulator," Energies, MDPI, vol. 13(19), pages 1-17, September.
    15. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    16. Daniel Sousa-Dias & Daniel Amyot & Ashkan Rahimi-Kian & John Mylopoulos, 2023. "A Review of Cybersecurity Concerns for Transactive Energy Markets," Energies, MDPI, vol. 16(13), pages 1-32, June.
    17. Denis Stanescu & Angela Digulescu & Cornel Ioana & Alexandru Serbanescu, 2021. "Entropy-Based Characterization of the Transient Phenomena—Systemic Approach," Mathematics, MDPI, vol. 9(6), pages 1-14, March.
    18. Zio, Enrico, 2016. "Challenges in the vulnerability and risk analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 137-150.
    19. Ji, Xingpei & Wang, Bo & Liu, Dichen & Dong, Zhaoyang & Chen, Guo & Zhu, Zhenshan & Zhu, Xuedong & Wang, Xunting, 2016. "Will electrical cyber–physical interdependent networks undergo first-order transition under random attacks?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 460(C), pages 235-245.
    20. Joshua Holstein & Max Schemmer & Johannes Jakubik & Michael Vössing & Gerhard Satzger, 2023. "Sanitizing data for analysis: Designing systems for data understanding," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-18, December.

    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:16:y:2023:i:17:p:6332-:d:1230220. 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.