Relevance of the Calculated Parameters PD-Defect Specific Risk and PD-Identification Confidence for Risk Assessment in GIS

Aschenbrenner, D.; Dreisbusch, K.; Kranz, H.-G.

doi:10.1109/icpadm.2006.284147

Cited by 2 publications

(1 citation statement)

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“…In order to comprehensively analyze the partial discharge condition in GIS and evaluate its severity, it is necessary to integrate the status information of the equipment [12], including measured data on partial discharge, equipment operating parameters, etc. According to a large number of live detection cases of substations provided by power companies in different regions, this paper constructs a data set of GIS failure cases.…”

Section: B Data Set Establishmentmentioning

confidence: 99%

Severity Evaluation of UHF Signals of Partial Discharge in GIS Based on Semantic Analysis

Meng

Song

Dai

et al. 2022

IEEE Trans. Power Delivery

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The severity evaluation of UHF signals of partial discharge in GIS is helpful to formulate a maintenance strategy in time, and improve the reliability of power system operation. Most of the evaluation methods are based on structured data, which cannot fully characterize the state of the equipment. In this paper, a method for evaluating the severity of UHF signals of partial discharge in GIS based on semantic analysis is presented. It comprehensively considers the influence of structured data and unstructured text data on the state of equipment, including measured data on partial discharge, relevant information of defects, and equipment operating parameters. Firstly, the severity of UHF signals of partial discharge is defined. According to the on-site detection of substations, a data set containing equipment detection reports and PRPS data is established. Aiming at semantic analysis, Word Embedding is used to associate and encode textual information to reduce the subjectivity of the encoding. Measured data on partial discharge is also combined and analyzed for evaluation. The method proposed is used for case analysis and compared with other methods. The results show that the comprehensive utilization of structured data and unstructured text data can reflect the state of equipment more comprehensively and truthfully, and improve the accuracy of the results.

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Section: B Data Set Establishmentmentioning

confidence: 99%