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

Muhammad Sharil Yahaya, Norhafiz Azis, Amran Mohd Selva, Mohd Zainal Abidin Ab Kadir, Jasronita Jasni, Emran Jawad Kadim, Mohd Hendra Hairi and Young Zaidey Yang Ghazali
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Muhammad Sharil Yahaya: Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Norhafiz Azis: Centre for Electromagnetic and Lightning Protection, 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
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

Energies, 2018, vol. 11, issue 8, 1-14

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.

Keywords: transformers; Health Index (HI); Markov Model (MM); transition probabilities; frequency of transition; prediction interval; maintenance cost; maintenance policy model (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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