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Asset Management Support Tool for Energy Systems using AHP and Monte Carlo Methods applied to Power Transformers

Author

Listed:
  • Filipe Possatti Campanhola

    (Electrical Engineering Graduate Program, Federal University of Santa Maria-UFSM, Santa Maria, Brazil,)

  • Jones Luís Schaefer

    (Production and Systems Engineering Graduate Program, Pontifical Catholic University of Paraná-PUCPR, Curitiba, Brazil,)

  • Rodinei Carraro

    (CPFL Transmissão, Canoas, Brazil,)

  • Julio Cezar Mairesse Siluk

    (Production Engineering Graduate Program, Federal University of Santa Maria-UFSM, Santa Maria, Brazil.)

  • Tiago Bandeira Marchesan

    (Electrical Engineering Graduate Program, Federal University of Santa Maria-UFSM, Santa Maria, Brazil,)

Abstract

The assets of electric power transmission systems are characterized by their high cost and complexity, leading utilities to seek ways to improve the efficiency and economic-financial performance of these assets. Thus, this article proposes a tool to support asset management for electricity transmission systems. This tool considers the useful life of the equipment, its importance to the system, financial aspects, and the forecast of electricity demand. An evaluation of the criteria that impact decision-making on the replacement of assets with specialists was carried out. Thus, the tool uses the Analytic Hierarchy Process method to classify the most critical equipment in the system. For analysis of future scenarios, the Monte Carlo Method was incorporated into the tool to simulate the behavior of equipment during a defined time horizon. As a result, the tool presents a ranking of the most critical equipment in the system under analysis within the simulated time horizon. The tool was applied in a case study with real data in the power transformer of a Brazilian utility. The tool helps in decision-making indicating changes that may be made in the period under review, their likely impact on equipment loading, and the list of critical transformers in the system.

Suggested Citation

  • Filipe Possatti Campanhola & Jones Luís Schaefer & Rodinei Carraro & Julio Cezar Mairesse Siluk & Tiago Bandeira Marchesan, 2023. "Asset Management Support Tool for Energy Systems using AHP and Monte Carlo Methods applied to Power Transformers," International Journal of Energy Economics and Policy, Econjournals, vol. 13(6), pages 441-451, November.
    • Handle: RePEc:eco:journ2:2023-06-46
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    References listed on IDEAS

    as
    1. GRABISCH, Michel & LABREUCHE, Christophe & RIDAOUI, Mustapha, 2019. "On importance indices in multicriteria decision making," European Journal of Operational Research, Elsevier, vol. 277(1), pages 269-283.
    2. Wang, Jiang-Jiang & Jing, You-Yin & Zhang, Chun-Fa & Zhao, Jun-Hong, 2009. "Review on multi-criteria decision analysis aid in sustainable energy decision-making," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(9), pages 2263-2278, December.
    3. Schaefer, Jones Luís & Mairesse Siluk, Julio Cezar & Stefan de Carvalho, Patrícia & Maria de Miranda Mota, Caroline & Pinheiro, José Renes & Nuno da Silva Faria, Pedro & Gouvea da Costa, Sergio Eduard, 2023. "A framework for diagnosis and management of development and implementation of cloud-based energy communities - Energy cloud communities," Energy, Elsevier, vol. 276(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Electric Power System; Asset Management; AHP; Monte Carlo Method; Power Transformers Management;
    All these keywords.

    JEL classification:

    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • L97 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Utilities: General
    • L64 - Industrial Organization - - Industry Studies: Manufacturing - - - Other Machinery; Business Equipment; Armaments

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