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Open AccessArticle

Effect of Pre-Determined Maintenance Repair Rates on the Health Index State Distribution and Performance Condition Curve Based on the Markov Prediction Model for Sustainable Transformers Asset Management Strategies

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Centre for Electromagnetic and Lightning Protection, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
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Faculty of Engineering Technology, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia
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Institute of Advanced Technology (ITMA), Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia
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Institute of Power Engineering (IPE), Universiti Tenaga Nasional, 43000 Kajang, Selangor, Malaysia
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Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, 76100 Durian Tunggal, Melaka, Malaysia
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Distribution Division, Tenaga Nasional Berhad, Wisma TNB, Jalan Timur, 46200 Petaling Jaya, Selangor, Malaysia
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TNB Research Sdn. Bhd., No. 1, Lorong Ayer Itam, Kawasan Institut Penyelidikan, 43000 Kajang, Selangor, Malaysia
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Authors to whom correspondence should be addressed.
Sustainability 2018, 10(10), 3399; https://doi.org/10.3390/su10103399
Received: 9 August 2018 / Revised: 17 August 2018 / Accepted: 23 August 2018 / Published: 25 September 2018
(This article belongs to the Section Sustainable Engineering and Science)
This paper presents an investigation of the condition state distribution and performance condition curve of the transformer population under different pre-determined maintenance repair rates based on the Markov Prediction Model (MPM). In total, 3195 oil samples from 373 transformers with an age between one and 25 years were tested. The previously computed Health Index (HI) prediction model of the transformer population based on MPM utilizing the nonlinear minimization technique was employed in this study. The transition probabilities for each of the states were updated based on 10%, 20% and 30% pre-determined maintenance repair rates for the sensitivity study. Next, the HI state distribution and performance condition curve were analyzed based on the Markov chain algorithm. Based on the case study, it is found that the pre-determined maintenance repair rates can affect the HI state distribution and improve the performance condition curve. The 30% pre-determined maintenance repair rate gives the highest impact, especially for the transformer population at state 4 (poor). Overall, the average percentage of change for all HI state distributions is 16.48%. A clear improvement of HI state distribution is found at state 4 (poor) where the highest percentage can be up to 63.25%. View Full-Text
Keywords: transformers; Health Index (HI); Markov Prediction Model (MPM); transition probabilities; nonlinear minimization; pre-determined maintenance repair rate; state distribution; performance condition curve transformers; Health Index (HI); Markov Prediction Model (MPM); transition probabilities; nonlinear minimization; pre-determined maintenance repair rate; state distribution; performance condition curve
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Yahaya, M.S.; Azis, N.; Mohd Selva, A.; Ab Kadir, M.Z.A.; Jasni, J.; Hairi, M.H.; Yang Ghazali, Y.Z.; Talib, M.A. Effect of Pre-Determined Maintenance Repair Rates on the Health Index State Distribution and Performance Condition Curve Based on the Markov Prediction Model for Sustainable Transformers Asset Management Strategies. Sustainability 2018, 10, 3399.

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