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Ageing estimation models for lightly loaded distribution power transformers
Thesis (MEng)--Stellenbosch University, 2018.
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2018
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| _version_ | 1867614117517328384 |
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| access_status_str | Open Access |
| author | Mukuddem, Mohamed Ziyaad |
| author2 | Jooste, J. L. |
| author_browse | Jooste, J. L. Mukuddem, Mohamed Ziyaad |
| author_facet | Jooste, J. L. Mukuddem, Mohamed Ziyaad |
| author_sort | Mukuddem, Mohamed Ziyaad |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (MEng)--Stellenbosch University, 2018. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/103456 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:46:56.603Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/103456 Ageing estimation models for lightly loaded distribution power transformers Mukuddem, Mohamed Ziyaad Jooste, J. L. Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. Electric transformers Asset-liability management Furanics Condition monitoring (Structural engineering) Genetic Algorithm Ageing Model UCTD Thesis (MEng)--Stellenbosch University, 2018. ENGLISH ABSTRACT: Power transformers form an integral part of present day electricity networks. They allow for power to efficiently be transported over vast distances. They are however one of the most expensive assets within the distribution network. In order to maximise return on investment for these assets, transformer owners need to ensure that they operate for as long as possible. The ageing of a transformer is based primarily on the condition of the solid insulation inside the transformer. There are various ageing models which attempt to predict the ageing of a transformer based on parameters such as hot-spot temperature, oxygen and moisture content. Typical distribution networks are designed with transformer redundancy. In these networks, the full load of a substation is typically shared across two or more transformers. This results in individual transformers being lightly loaded (<50%). This study investigates the accuracy of the ageing models presented on a fleet of twenty distribution power transformers. The study compiles an algorithm which carries out two main functions. The first is to determine the hot-spot temperature based on loading. The second is to predict the loss-of-life based on the various ageing models identified. This predicted loss-of-life value is compared to measured loss-of-life values in order to determine which model produces the most accurate results. Using these results, the study goes further to modify these ageing models in an attempt to improve the accuracy thereof. These modified model’s accuracy rates are compared to each other as well as the initial ageing models to identify if any improvement in accuracy is produced. A modified output model is produced which increases the accuracy of the loss-of-life prediction for lightly loaded transformers. The modified model utilises the historic average hot-spot operating temperature in order to determine the ageing rate. This can be utilised by asset managers of power transformers in distribution networks. AFRIKAANSE OPSOMMING: Transformators is integrale komponente van elektriese verspreidingsnetwerke – daarsonder kan elektriese krag nie effektief oor lang afstande gevoer word nie. Transfomators kom egter ook teen ‘n koste wat dit in terme van finansiële bate waarde klassifiseer onder die duurste komponente van ‘n kragstelsel. Dit is in die belang van die bate eienaars dat transformators ‘n lewensduur het wat die belegging nie alleen net regverdig nie, maar maksimeer. Die begrip van veroudering van ‘n transformator word hoofsaaklik gebaseer op die toestand van die elektriese isoleringsmateriaal in vastestof vorm wat intern tot die eenheid gebruik word. Bestaande modelle wat poog om die staat van veroudering te voorspel, is gebaseer op parameters soos warmste temperatuur, suurstof- en voginhoud. Transformator oortolligheid is ingebou die ontwerp van elektriese netwerke en derhalwe word die volle elektriese las tipies tussen twee of meer transformators gedeel. Die resultaat hiervan is dat individuele transformators lig belas word (<50%). Hierdie studie ondersoek die akkuraatheid van verouderingsmodelle soos toegepas op twintig distribusievlak transformators. ‘n Algoritme word saamgestel wat twee hoofsaaklike funksies uitvoer. Eerstens word ‘n warmste temperatuur bepaal, gebaseer op die belading. Tweedens word die verlies aan lewensduurte voorspel uit die verskillende geïdentifiseerde modelle. Die voorspelde verlies aan lewensduurte word vergelyk met die werklike verlies om sodoende die model met die mees akkurate resultate te identifiseer. Die studie gebruik dan voorts hierdie resultate om die verouderingsmodelle te wysig met die doel om die akkuraatheid daarvan te verbeter. Die mate waartoe die gewysigde modelle se akkuraatheid verander, word met mekaar sowel as met die aanvanklike modelle vergelyk om vas te stel of enige verbetering in akkuraatheid bereik is. Die resultaat is 'n gewysigde uitset model met verhoogde akkuraatheid in die voorspelde verlies aan lewensduur vir ligbelaste transformators. Die gewysigde model gebruik geskiedenis gemiddelde warmste bedryfstemperatuur om die verouderingstempo te bepaal. Die model vind toepassing in die bestuur van transformator bates in distribusie netwerke. 2018-02-21T10:06:30Z 2018-04-09T06:57:21Z 2018-02-21T10:06:30Z 2018-04-09T06:57:21Z 2018-03 Thesis http://hdl.handle.net/10019.1/103456 en_ZA Stellenbosch University 123 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Electric transformers Asset-liability management Furanics Condition monitoring (Structural engineering) Genetic Algorithm Ageing Model UCTD Mukuddem, Mohamed Ziyaad Ageing estimation models for lightly loaded distribution power transformers |
| title | Ageing estimation models for lightly loaded distribution power transformers |
| title_full | Ageing estimation models for lightly loaded distribution power transformers |
| title_fullStr | Ageing estimation models for lightly loaded distribution power transformers |
| title_full_unstemmed | Ageing estimation models for lightly loaded distribution power transformers |
| title_short | Ageing estimation models for lightly loaded distribution power transformers |
| title_sort | ageing estimation models for lightly loaded distribution power transformers |
| topic | Electric transformers Asset-liability management Furanics Condition monitoring (Structural engineering) Genetic Algorithm Ageing Model UCTD |
| url | http://hdl.handle.net/10019.1/103456 |
| work_keys_str_mv | AT mukuddemmohamedziyaad ageingestimationmodelsforlightlyloadeddistributionpowertransformers |