Development and implementation of risk indicator for power transformers based on electrical measurements

Poiss, Gints; Vītoliņa, Sandra

doi:10.1109/epe.2017.7967289

Cited by 2 publications

(3 citation statements)

References 3 publications

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“…This paper is an extension of the results disseminated in the international conference paper relating to the development of risk indicator for power transformers based on electrical measurements [1]. This risk indicator is part of a condition indexing algorithm that allows categorizing a large volume of technical data obtained during operation and maintenance of a power transformer into discrete risk categories.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore as additional criterion for the OLTC assessment -the dynamic resistance measurement (DRM) is proposed [1] evaluating two parameters form test report: transition time, ms, and current ripple change I N1,2, %. The proposed limit values E1 and E5 shown in Table 2 are assigned on basis of [12] …”

Section: Oltcmentioning

confidence: 99%

“…It causes difficulties if evaluation is based on traditional comparative analysis to a factory test. In order to use results of a single measurement in this algorithm, limits based on statistical data and recommendations of [9] and performed study of measurement history of no-load losses from 100 transformers [1].…”

Section: Winding and Corementioning

confidence: 99%

See 2 more Smart Citations

Development of Indicators for Technical Condition Indexing of Power Transformers

Poiss¹,

Vītoliņa²,

Marks³

2018

Adv. sci. technol. eng. syst. j.

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Section: Introductionmentioning

confidence: 99%

Section: Oltcmentioning

confidence: 99%

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Development of Indicators for Technical Condition Indexing of Power Transformers

Poiss¹,

Vītoliņa²,

Marks³

2018

Adv. sci. technol. eng. syst. j.

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Fuzzy Algorithms for Diagnosis of Furnace Transformer Insulation Condition

et al. 2022

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Implementation of the smart transformer concept is critical for the deployment of IIoT-based smart grids. Top manufacturers of power electrics develop and adopt online monitoring systems. Such systems become part of high-voltage grid and unit transformers. However, furnace transformers are a broad category that this change does not affect yet. At the same time, adoption of diagnostic systems for furnace transformers is relevant because they are a heavy-duty application with no redundancy. Creating any such system requires a well-founded mathematical analysis of the facility’s condition, carefully selected diagnostic parameters, and setpoints thereof, which serve as the condition categories. The goal hereof was to create an expert system to detect insulation breach and its expansion as well as to evaluate the risk it poses to the system; the core mechanism is mathematical processing of trends in partial discharge (PD). We ran tests on a 26-MVA transformer installed on a ladle furnace at a steelworks facility. The transformer is equipped with a versatile condition monitoring system that continually measures apparent charge and PD intensity. The objective is to identify the condition of the transformer and label it with one of the generally recognized categories: Normal, Poor, Critical. The contribution of this paper consists of the first ever validation of a single generalized metric that describes the condition of transformer insulation based on the online monitoring of the PD parameters. Fuzzy logic algorithms are used in mathematical processing. The proposal is to generalize the set of diagnostic variables to a single deterministic parameter: insulation state indicator. The paper provides an example of calculating it from the apparent charge and PD power readings. To measure the indicativeness of individual parameters for predicting further development of a defect, the authors developed a method for testing the diagnostic sensitivity of these parameters to changes in the condition. The method was tested using trends in readings sampled whilst the status was degrading from Normal to Critical. The paper also shows a practical example of defect localization. The recommendation is to broadly use the method in expert systems for high-voltage equipment monitoring.

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Development and implementation of risk indicator for power transformers based on electrical measurements

Cited by 2 publications

References 3 publications

Development of Indicators for Technical Condition Indexing of Power Transformers

Development of Indicators for Technical Condition Indexing of Power Transformers

Fuzzy Algorithms for Diagnosis of Furnace Transformer Insulation Condition

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