Academic Journal
Stratifying transformer defects through modelling and simulation of thermal decomposition of insulating mineral oil
| Title: | Stratifying transformer defects through modelling and simulation of thermal decomposition of insulating mineral oil |
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| Authors: | A. Manjula, Sangeetha S, Mustafa Musa Jaber, Hamad Mohamad A.A, Santosh Kumar Sahu, Rajesh Verma, Prashant Vats |
| Source: | Automatika, Vol 64, Iss 4, Pp 733-747 (2023) |
| Publisher Information: | Taylor & Francis Group, 2023. |
| Publication Year: | 2023 |
| Collection: | LCC:Automation |
| Subject Terms: | Dissolved gas, Insulating mineral oil, incipient defects, Sum of squares of the relative residuals, Control engineering systems. Automatic machinery (General), TJ212-225, Automation, T59.5 |
| More Details: | The current work aims to propose an adequate thermodynamic model, in addition to proposing and evaluating two composite models for the thermal decomposition of insulating mineral oil (IMO), considering that the models based on classical diagnostic methods do not have the ability to satisfactorily reproduce empirical data. The simulation results obtained using the proposed model showed better agreement with the presented data than the results obtained using classical models. The proposed model was also used in the development of a phenomenological based diagnostic method. The characteristics of this new phenomenological proposal and the classical diagnostic methods of dissolved gas analysis are compared and discussed; the proposed method showed better performance when compared to Rogers, Doernenburg, or IEC and equivalent performance to Duval triangle method commonly used in this field of knowledge. The general procedure for applying the new diagnostic method is also described. In order to account for the event's dynamics, the suggested model in particular made it feasible to replicate intermediate scenes of equilibrium C(s). Compared to the findings from the classical models found in the literature, the two-dimensional simulation results generated with this model demonstrated a better agreement with the actual data. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 00051144 1848-3380 0005-1144 |
| Relation: | https://doaj.org/toc/0005-1144; https://doaj.org/toc/1848-3380 |
| DOI: | 10.1080/00051144.2023.2197821 |
| Access URL: | https://doaj.org/article/38a7c1eed27d4b4fb548cd610c1745a9 |
| Accession Number: | edsdoj.38a7c1eed27d4b4fb548cd610c1745a9 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 00051144 18483380 |
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| DOI: | 10.1080/00051144.2023.2197821 |
| Published in: | Automatika |
| Language: | English |