Application of Markov Model to estimate individual condition parameters for transformers
This paper presents a study to estimate individual condition parameters of the transformer population based on Markov Model (MM). The condition parameters under study were hydrogen (H2), methane (CH4), acetylene (C2H2), ethylene (C2H4), ethane (C2H6), carbon monoxide (CO), carbon dioxide (CO2), diel...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Multidisciplinary Digital Publishing Institute (MDPI)
2018
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/73178/1/MARKOV.pdf |
| _version_ | 1825950173377855488 |
|---|---|
| author | Azis, Norhafiz Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Mohd Selva, Amran Yahaya, Muhammad Sharil Yang Ghazali, Young Zaidey Talib, Mohd Aizam |
| author_facet | Azis, Norhafiz Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Mohd Selva, Amran Yahaya, Muhammad Sharil Yang Ghazali, Young Zaidey Talib, Mohd Aizam |
| author_sort | Azis, Norhafiz |
| collection | UPM |
| description | This paper presents a study to estimate individual condition parameters of the transformer population based on Markov Model (MM). The condition parameters under study were hydrogen (H2), methane (CH4), acetylene (C2H2), ethylene (C2H4), ethane (C2H6), carbon monoxide (CO), carbon dioxide (CO2), dielectric breakdown voltage, interfacial tension, colour, acidity, water content, and 2-furfuraldehyde (2-FAL). First, the individual condition parameter of the transformer population was ranked and sorted based on recommended limits as per IEEE Std. C57. 104-2008 and IEEE Std. C57.106-2015. Next, the mean for each of the condition parameters was computed and the transition probabilities for each condition parameters were obtained based on non-linear optimization technique. Next, the future states probability distribution was computed based on the MM prediction model. Chi-square test and percentage of absolute error analysis were carried out to find the goodness-of-fit between predicted and computed condition parameters. It is found that estimation for majority of the individual condition parameter of the transformer population can be carried out by MM. The Chi-square test reveals that apart from CH4 and C2H4, the condition parameters are outside the rejection region that indicates agreement between predicted and computed values. It is also observed that the lowest and highest percentages of differences between predicted and computed values of all the condition parameters are 81.46% and 98.52%, respectively. |
| first_indexed | 2024-03-06T10:10:34Z |
| format | Article |
| id | upm.eprints-73178 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T10:10:34Z |
| publishDate | 2018 |
| publisher | Multidisciplinary Digital Publishing Institute (MDPI) |
| record_format | dspace |
| spelling | upm.eprints-731782020-12-01T21:17:48Z http://psasir.upm.edu.my/id/eprint/73178/ Application of Markov Model to estimate individual condition parameters for transformers Azis, Norhafiz Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Mohd Selva, Amran Yahaya, Muhammad Sharil Yang Ghazali, Young Zaidey Talib, Mohd Aizam This paper presents a study to estimate individual condition parameters of the transformer population based on Markov Model (MM). The condition parameters under study were hydrogen (H2), methane (CH4), acetylene (C2H2), ethylene (C2H4), ethane (C2H6), carbon monoxide (CO), carbon dioxide (CO2), dielectric breakdown voltage, interfacial tension, colour, acidity, water content, and 2-furfuraldehyde (2-FAL). First, the individual condition parameter of the transformer population was ranked and sorted based on recommended limits as per IEEE Std. C57. 104-2008 and IEEE Std. C57.106-2015. Next, the mean for each of the condition parameters was computed and the transition probabilities for each condition parameters were obtained based on non-linear optimization technique. Next, the future states probability distribution was computed based on the MM prediction model. Chi-square test and percentage of absolute error analysis were carried out to find the goodness-of-fit between predicted and computed condition parameters. It is found that estimation for majority of the individual condition parameter of the transformer population can be carried out by MM. The Chi-square test reveals that apart from CH4 and C2H4, the condition parameters are outside the rejection region that indicates agreement between predicted and computed values. It is also observed that the lowest and highest percentages of differences between predicted and computed values of all the condition parameters are 81.46% and 98.52%, respectively. Multidisciplinary Digital Publishing Institute (MDPI) 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/73178/1/MARKOV.pdf Azis, Norhafiz and Jasni, Jasronita and Ab Kadir, Mohd Zainal Abidin and Mohd Selva, Amran and Yahaya, Muhammad Sharil and Yang Ghazali, Young Zaidey and Talib, Mohd Aizam (2018) Application of Markov Model to estimate individual condition parameters for transformers. Energies, 11 (8). pp. 1-16. ISSN 1996-1073 https://www.mdpi.com/1996-1073/11/8/2114 10.3390/en11082114 |
| spellingShingle | Azis, Norhafiz Jasni, Jasronita Ab Kadir, Mohd Zainal Abidin Mohd Selva, Amran Yahaya, Muhammad Sharil Yang Ghazali, Young Zaidey Talib, Mohd Aizam Application of Markov Model to estimate individual condition parameters for transformers |
| title | Application of Markov Model to estimate individual condition parameters for transformers |
| title_full | Application of Markov Model to estimate individual condition parameters for transformers |
| title_fullStr | Application of Markov Model to estimate individual condition parameters for transformers |
| title_full_unstemmed | Application of Markov Model to estimate individual condition parameters for transformers |
| title_short | Application of Markov Model to estimate individual condition parameters for transformers |
| title_sort | application of markov model to estimate individual condition parameters for transformers |
| url | http://psasir.upm.edu.my/id/eprint/73178/1/MARKOV.pdf |
| work_keys_str_mv | AT azisnorhafiz applicationofmarkovmodeltoestimateindividualconditionparametersfortransformers AT jasnijasronita applicationofmarkovmodeltoestimateindividualconditionparametersfortransformers AT abkadirmohdzainalabidin applicationofmarkovmodeltoestimateindividualconditionparametersfortransformers AT mohdselvaamran applicationofmarkovmodeltoestimateindividualconditionparametersfortransformers AT yahayamuhammadsharil applicationofmarkovmodeltoestimateindividualconditionparametersfortransformers AT yangghazaliyoungzaidey applicationofmarkovmodeltoestimateindividualconditionparametersfortransformers AT talibmohdaizam applicationofmarkovmodeltoestimateindividualconditionparametersfortransformers |