Optimization of transformer oil blended with natural ester oils using Taguchi-based grey relational analysis. (15th March 2021)
- Record Type:
- Journal Article
- Title:
- Optimization of transformer oil blended with natural ester oils using Taguchi-based grey relational analysis. (15th March 2021)
- Main Title:
- Optimization of transformer oil blended with natural ester oils using Taguchi-based grey relational analysis
- Authors:
- Senthilkumar, Subburaj
Karthick, Alagar
Madavan, R.
Arul Marcel Moshi, A.
Sundara Bharathi, S.R.
Saroja, S.
Sowmya Dhanalakshmi, C. - Abstract:
- Highlights: Novel optimization technique for optimization of the transformer oil. Transformer oil blended with sunflower oil, palm oil, rapeseed oil and olive oil. The properties of the proposed mineral is analyzed with Taguchi method. Mineral oil with sunflower oil blending found to be an optimum mixture. Abstract: The objective of the work is to improve the performance of mineral oil. To enhance the performance, mineral oil is blended with natural ester oils such as sunflower oil, palm oil, rapeseed oil and Olive oil. The key parameters of the blending mixtures are measured such as breakdown voltage, viscosity, flash point, fire point and acidity as per standards. In order to verify the repeatability and reproducibility of the above parameters, repeated measurements are taken. With the increase in mixing ratio, the performance of samples gets increased to some extent, after that, it started decreasing. The selection of optimal sample concentration based on the considered parameters is quite tricky. Therefore, it is vital to determine the optimal sample concentration based on the enhanced electrical, physical and thermal properties with respect to the mixture concentration. In this work, the selection of optimal mixed liquid insulation is performed by a grey relational analysis (GRA) method after carefully measuring the properties. It determines, Mineral oil and Sunflower oil mixing ratio 10:90 produces desirable performance compared to other samples. Validation has alsoHighlights: Novel optimization technique for optimization of the transformer oil. Transformer oil blended with sunflower oil, palm oil, rapeseed oil and olive oil. The properties of the proposed mineral is analyzed with Taguchi method. Mineral oil with sunflower oil blending found to be an optimum mixture. Abstract: The objective of the work is to improve the performance of mineral oil. To enhance the performance, mineral oil is blended with natural ester oils such as sunflower oil, palm oil, rapeseed oil and Olive oil. The key parameters of the blending mixtures are measured such as breakdown voltage, viscosity, flash point, fire point and acidity as per standards. In order to verify the repeatability and reproducibility of the above parameters, repeated measurements are taken. With the increase in mixing ratio, the performance of samples gets increased to some extent, after that, it started decreasing. The selection of optimal sample concentration based on the considered parameters is quite tricky. Therefore, it is vital to determine the optimal sample concentration based on the enhanced electrical, physical and thermal properties with respect to the mixture concentration. In this work, the selection of optimal mixed liquid insulation is performed by a grey relational analysis (GRA) method after carefully measuring the properties. It determines, Mineral oil and Sunflower oil mixing ratio 10:90 produces desirable performance compared to other samples. Validation has also been carried out on the optimized sample concentration. It is concluded that grey relational analysis is a possible method to determine the optimal sample concentration of mixed liquid insulation. … (more)
- Is Part Of:
- Fuel. Volume 288(2021)
- Journal:
- Fuel
- Issue:
- Volume 288(2021)
- Issue Display:
- Volume 288, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 288
- Issue:
- 2021
- Issue Sort Value:
- 2021-0288-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-03-15
- Subjects:
- Mixed oil -- Performance Characteristics -- Optimization -- Taguchi -- GRA
Fuel -- Periodicals
Coal -- Periodicals
Coal
Fuel
Periodicals
662.6 - Journal URLs:
- http://www.sciencedirect.com/science/journal/latest/00162361 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.fuel.2020.119629 ↗
- Languages:
- English
- ISSNs:
- 0016-2361
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4048.000000
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