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

Hamid Mirshekali, Lasse Kappel Mortensen and Hamid Reza Shaker

Applied Energy, 2024, vol. 358, issue C, No S0306261923019207

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.

Keywords: Epsilon-constraint method; Multi-objective optimization; Predictive asset management; Underground cable (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1016/j.apenergy.2023.122556

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