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Reliability-aware multi-objective approach for predictive asset management: A Danish distribution grid case study

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  • Mirshekali, Hamid
  • Mortensen, Lasse Kappel
  • Shaker, Hamid Reza

Abstract

The transition towards sustainable practices and a reliable electricity grid accommodates the rising electrification of the heating and transportation sectors. Aging, environmental factors, and operational conditions of electrical grid infrastructure contribute to a higher likelihood of faults. This leads to a reduced level of reliability, emphasizing the importance of renewing electrical grid infrastructure, particularly underground cables. Optimally replacing cables is essential, taking into account various factors like reducing the fault probability, minimizing the cost of power outages, and enhancing reliability within the budgetary constraint. This paper introduces an innovative methodology to predictive asset management for replacing underground cables using multi-objective optimization approach. Three objective functions are formulated: number of replaced cables, cost of power outages, and interruption-related index, which is determined through metrics like SAIFI, SAIDI, and ASIDI. These objectives are modeled as mixed-integer programming creating a multi-objective optimization problem, which is addressed using the epsilon-constraint approach. The optimization model identifies the cables that should be replaced within the budget constraint, aiming to optimize the objectives. The effectiveness of this approach is assessed using a real Danish distribution grid. The findings indicate that, compared to methods based on the cable age, fault vulnerability, and risk assessment, the proposed method demonstrates superior performance in terms of reliability metrics and power outage cost.

Suggested Citation

  • Mirshekali, Hamid & Mortensen, Lasse Kappel & Shaker, Hamid Reza, 2024. "Reliability-aware multi-objective approach for predictive asset management: A Danish distribution grid case study," Applied Energy, Elsevier, vol. 358(C).
  • Handle: RePEc:eee:appene:v:358:y:2024:i:c:s0306261923019207
    DOI: 10.1016/j.apenergy.2023.122556
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    References listed on IDEAS

    as
    1. 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.
    2. Mortensen, Lasse Kappel & Shaker, Hamid Reza & Veje, Christian T., 2022. "Relative fault vulnerability prediction for energy distribution networks," Applied Energy, Elsevier, vol. 322(C).
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    5. Tanachai Somsak & Thanapong Suwanasri & Cattareeya Suwanasri, 2022. "Remaining Useful Life Estimation for Underground Cable Systems Based on Historical Health Index," Energies, MDPI, vol. 15(24), pages 1-15, December.
    6. Alex Valenzuela & Esteban Inga & Silvio Simani, 2019. "Planning of a Resilient Underground Distribution Network Using Georeferenced Data," Energies, MDPI, vol. 12(4), pages 1-20, February.
    7. LaCommare, Kristina Hamachi & Eto, Joseph H., 2006. "Cost of power interruptions to electricity consumers in the United States (US)," Energy, Elsevier, vol. 31(12), pages 1845-1855.
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