A Maintenance Cost Study of Transformers Based on Markov Model Utilizing Frequency of Transition Approach
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
Institute of Advanced Technology (ITMA), Universiti Putra Malaysia, Serdang 43400, Selangor, Malaysia
Institute of Power Engineering (IPE), Universiti Tenaga Nasional, Kajang 43000, Selangor, Malaysia
Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Melaka 76100, Malaysia
Distribution Division, Tenaga Nasional Berhad, Wisma TNB, Jalan Timur, Petaling Jaya 46200, Selangor, Malaysia
Author to whom correspondence should be addressed.
Energies 2018, 11(8), 2006; https://doi.org/10.3390/en11082006
Received: 11 June 2018 / Revised: 22 June 2018 / Accepted: 25 June 2018 / Published: 2 August 2018
(This article belongs to the Section Electrical Power and Energy System)
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.