Condition assessment of power transformer using SVM based on DGA

Singh, Jagdeep; Kumari, Priyam; Kaur, Kulraj; Swami, Ankit Kumar

doi:10.1109/aic-mitcsa.2016.7759957

Cited by 6 publications

(1 citation statement)

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“…At the same time, the concept of expert validity material element is introduced to make the weight determination more reasonable. In reference [24], based on DGA and SVM, the transformer state is evaluated, and the oil-immersed transformer is taken as an example for verification. Reference [25] introduces a transformer fleet monitoring solution to help the end user to group transformer assets and react accordingly to monitored situations [25].…”

Section: Introductionmentioning

confidence: 99%

An Assessment of the Condition of Distribution Network Equipment Based on Large Data Fuzzy Decision-Making

Wang

Zhao

2020

Energies

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As one of the most important components of power grid, a distribution network is the most vulnerable part in the face of various uncertainties, and influences the stability and economy of a power system. In this paper, the operational information, hardware information and human factors were considered, and a state evaluation model of multi-source information fusion was established. Based on big data fuzzy iteration method and a weighted expert library, a weighted distribution of multi-source information was obtained, and an equipment condition assessment was carried out reasonably. Taking the distribution transformer as an example, the assessment showed that fusion of multi-source information presented in this paper is more comprehensive, and has the ability to reflect the state of equipment. The method proposed in this paper can accurately judge the running state of distribution equipment based on all kinds of information, and provides a reference for the follow-up power marketing for the status assessment of the user equipment.

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Section: Introductionmentioning

confidence: 99%