Response Characteristics of the Buchholz Relay and Novel Non-Electric-Parameter Protection Methods

Li, Boyu; Hao, Zhiguo; Li, Simeng; Pan, Shuyan; Xiong, Junhui; Zhang, Baohui

doi:10.1109/tpwrd.2023.3321773

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…It is observed that fuzzy logic approach is highly reliable over other methods, due to its operational speed of faults identification in modern power system transformers within 5.3 ms, with an accuracy ranging from 96%-99% depending on the sensitivity the fault. Differential protection 80%-90% Fast 50 ms-100 ms [21] Sequential kalman filter 85%-90% Moderate 500 ms-1 sec [17] Electrical transient analyser 70%-80% Slow 5 secs-10 secs [3] Dissolved gas analysis 60%-80% Slow 15 mins-30 mins [18] Buchholz relay 70%-80% Moderate 100 ms-500 ms [22] GA-XG boost classifier 90%-95% Fast 50 ms-100 ms [Proposed]…”

Section: Proposed Methods Comparison With Existing Methodsmentioning

confidence: 99%

“…Similarly, Mohammed et al [17], on transformer fault detection was proposed, yet, the approach suffers due to complexity, accuracy dependence on input data quality, potential modeling inaccuracies, and challenges in capturing real-world dynamics for effective optimization and fault diagnosis. In their paper Buchholz relay response and innovative non-electric-parameter protection, the approach detects internal faults through gas and oil anomalies, preventing catastrophic failures in transformers effectively [18]. Thus, it is limited to the detection of internal faults.…”

Section: Introductionmentioning

confidence: 99%

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Transformer faults identification via fuzzy logic approach

Dapshima,

Mishra,

Tyagi

2024

IJEECS

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The need for a constant electricity supply is at an alarming rate especially in the 21st century due to the high rate of increase in industrialization across the globe. Conventional protection schemes such as differential relays, Buchholz relay, and other techniques such as genetic algorithms and artificial neural networks, do not match the precision and reliability needed for transformer fault indentification, due to their complexity in computation, tedious training system, time consumption, and need the of human experts. The method proposed in this research is the use of a fuzzy inference system in detecting potential faults in power system transformers. The faults in the transformer were observed and analyzed using a simulation system of MATLAB/Simulink software. The suggested approach ensures swift identification of faults as it relies on if-then rules and only uses current and voltage measurements with 100% independence toward the power flow direction, making it highly reliable and simple to implement compared to other techniques for transformer fault identification.

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Section: Proposed Methods Comparison With Existing Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transformer faults identification via fuzzy logic approach

Dapshima,

Mishra,

Tyagi

2024

IJEECS

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“…However, the accuracy of light gas action protection has been low over the long term [ 11 , 12 ]. This is because its criterion is the volume of gas accumulation, which is easily influenced by non-fault factors such as trapped gas, leading to insufficient reliability of protection [ 13 , 14 ]. As a result, power departments in many countries, including Europe and North America, typically use light gas relays as a means of alarm.…”

Section: Introductionmentioning

confidence: 99%

Transformer Monitoring with Electromagnetic Energy Transmission and Wireless Sensing

Xu,

Shang,

et al. 2024

Sensors

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To ensure stable and normal transformer operation, light gas protection of the transformer Buchholz relay is essential. However, false alarms related to light gas protection are common, and troubleshooting them often requires on-site gas sampling by personnel. During this time, the transformer’s operating state may rapidly deteriorate, posing a safety threat to field staff. To tackle these challenges, this work presents the near-field, thin-sliced transformer monitoring system that uses Electromagnetic Energy Transmission and Wireless Sensing Device (ETWSD). The system leverages external wireless energy input to power gas monitoring sensors. Simultaneously, it employs Near-Field Communication to obtain real-time concentrations of light gases, along with the electrified state and temperature. In field testing conducted on transformer relays’ gas collection chambers, the ETWSD effortlessly monitors parameters within warning ranges, encompassing methane gas concentrations around 1000 ppm, leakage voltage ranging from 0–100 V, and relay working temperatures up to 90 °C. Additionally, to facilitate real-time diagnosis for electrical workers, we have developed an Android-based APP software that displays current light gas concentrations, leakage voltage collection values, and temperature, while also enabling threshold judgment, alarms, and data storage. The developed ETWSD is expected to aid on-site personnel in promptly and accurately evaluating transformer light gas protection error alarm faults. It provides a method for simultaneous, contactless, and rapid monitoring of multiple indicators.

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