Applied Complex Diagnostics and Monitoring of Special Power Transformers

被引:3
作者
Ivanov, Georgi [1 ,2 ]
Spasova, Anelia [3 ]
Mateev, Valentin [2 ]
Marinova, Iliana [2 ]
机构
[1] Centralna Energoremontna Baza EAD, Cerb TRAFO, Lokomotiv 1, Sofia 1220, Bulgaria
[2] Tech Univ Sofia, Dept Elect Apparat, Sofia 1797, Bulgaria
[3] Centralna Himicheska Lab Ltd, Lokomotiv 1, Sofia 1220, Bulgaria
关键词
applied diagnostics; transformer diagnostics; health index; power transformers; monitoring of power transformers; risk assessment of power transformers; predictive maintenance; DGA;
D O I
10.3390/en16052142
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
As a major component in electric power systems, power transformers are one of the most expensive and important pieces of electrical equipment. The trouble-free operation of power transformers is an important criterion for safety and stability in a power system. Technical diagnostics of electrical equipment are a mandatory part of preventing accidents and ensuring the continuity of the power supply. In this study, a complex diagnostic methodology was proposed and applied for special power transformers' risk estimation. Twenty special power transformers were scored with the proposed risk estimation methodology. For each transformer, dissolved gas analysis (DGA) tests, transformer oil quality analysis, visual inspections of all current equipment on-site and historical data for the operation of each electrical research were conducted. All data were collected and analyzed under historical records of malfunctioning events. Statistical data for expected fault risk, based on long-term records, with such types of transformers were used to make more precise estimations of the current state of each machine and expected operational resource. The calculated degree of insulation polymerization was made via an ANN-assisted predictive method. Assessment of the collected data was applied to allow detailed information of the state of the power transformer to be rated. A method for risk assessment and reliability estimation was proposed and applied, based on the health index (HI) for each transformer.
引用
收藏
页数:24
相关论文
共 45 条
  • [1] Application of Machine Learning in Transformer Health Index Prediction
    Alqudsi, Alhaytham
    El-Hag, Ayman
    [J]. ENERGIES, 2019, 12 (14)
  • [2] Machine learning for predictive maintenance scheduling of distribution transformers
    Alvarez Quinones, Laura Isabel
    Arturo Lozano-Moncada, Carlos
    Bravo Montenegro, Diego Alberto
    [J]. JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING, 2023, 29 (01) : 188 - 202
  • [3] [Anonymous], 2011, 600761 IEC
  • [4] [Anonymous], 2020, 602962020 IEC
  • [5] [Anonymous], 2003, 6202112003 EN INT EL
  • [6] [Anonymous], 2013, 604222013 IEC
  • [7] [Anonymous], 2022, 605992022 IEC
  • [8] [Anonymous], 1997, 608141997 IEC
  • [9] [Anonymous], 2004, 60247 IEC
  • [10] [Anonymous], 1995, 621995 IEEE