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A Maintenance Cost Study of Transformers Based on Markov Model Utilizing Frequency of Transition Approach

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  • Muhammad Sharil Yahaya

    (Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
    Faculty of Engineering Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Melaka 76100, Malaysia)

  • Norhafiz Azis

    (Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
    Institute of Advanced Technology (ITMA), Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Amran Mohd Selva

    (Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Mohd Zainal Abidin Ab Kadir

    (Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
    Institute of Power Engineering (IPE), Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia)

  • Jasronita Jasni

    (Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Emran Jawad Kadim

    (Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia)

  • Mohd Hendra Hairi

    (Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Melaka 76100, Malaysia)

  • Young Zaidey Yang Ghazali

    (Distribution Division, Tenaga Nasional Berhad, Wisma TNB, Jalan Timur, Petaling Jaya 46200, Selangor, Malaysia)

Abstract

In this paper, a maintenance cost study of transformers based on the Markov Model (MM) utilizing the Health Index (HI) is presented. In total, 120 distribution transformers of oil type (33/11 kV and 30 MVA) are examined. The HI is computed based on condition assessment data. Based on the HI, the transformers are arranged according to its corresponding states, and the transition probabilities are determined based on frequency of a transition approach utilizing the transformer transition states for the year 2013/2014 and 2012/2013. The future states of transformers are determined based on the MM chain algorithm. Finally, the maintenance costs are estimated based on future-state distribution probabilities according to the proposed maintenance policy model. The study shows that the deterioration states of the transformer population for the year 2015 can be predicted by MM based on the transformer transition states for the year 2013/2014 and 2012/2013. Analysis on the relationship between the predicted and actual computed numbers of transformers reveals that all transformer states are still within the 95% prediction interval. There is a 90% probability that the transformer population will reach State 1 after 76 years and 69 years based on the transformer transition states for the year 2013/2014 and 2012/2013. Based on the probability-state distributions, it is found that the total maintenance cost increases gradually from Ringgit Malaysia (RM) 5.94 million to RM 39.09 million based on transformer transition states for the year 2013/2014 and RM 37.56 million for the year 2012/2013 within the 20 years prediction interval, respectively.

Suggested Citation

  • Muhammad Sharil Yahaya & Norhafiz Azis & Amran Mohd Selva & Mohd Zainal Abidin Ab Kadir & Jasronita Jasni & Emran Jawad Kadim & Mohd Hendra Hairi & Young Zaidey Yang Ghazali, 2018. "A Maintenance Cost Study of Transformers Based on Markov Model Utilizing Frequency of Transition Approach," Energies, MDPI, vol. 11(8), pages 1-14, August.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2006-:d:161445
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    References listed on IDEAS

    as
    1. Si, Xiao-Sheng & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2011. "Remaining useful life estimation - A review on the statistical data driven approaches," European Journal of Operational Research, Elsevier, vol. 213(1), pages 1-14, August.
    2. Muhammad Sharil Yahaya & Norhafiz Azis & Mohd Zainal Abidin Ab Kadir & Jasronita Jasni & Mohd Hendra Hairi & Mohd Aizam Talib, 2017. "Estimation of Transformers Health Index Based on the Markov Chain," Energies, MDPI, vol. 10(11), pages 1-11, November.
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    Cited by:

    1. Mateusz Oszczypała & Jarosław Ziółkowski & Jerzy Małachowski, 2022. "Analysis of Light Utility Vehicle Readiness in Military Transportation Systems Using Markov and Semi-Markov Processes," Energies, MDPI, vol. 15(14), pages 1-24, July.

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