Efficiency and Cost Based Multi-optimization and Thermal/Electromagnetic Analyses of 3-Phase Dry-Type Transformer

Esenboga, Burak; Demirdelen, Tuğçe

doi:10.1080/03772063.2020.1732841

Cited by 13 publications

(4 citation statements)

References 18 publications

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“…Combined with the typical waveform of on-off overvoltage, the influence law of random parameters such as cut-off value and action time difference on overvoltage is analyzed. The theoretical analysis model of the threephase circuit breaker breaking the shunt reactor is built [8][9][10].…”

Section: Simulation Of Startingmentioning

confidence: 99%

Life Prediction of Dry Reactor Sensor Based on Deep Neural Network

et al. 2022

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In order to solve the problem of increasing the number and service life of a dry-type air core reactor and frequent interturn insulation faults, this paper proposes a life prediction method of a dry-type reactor sensor based on the deep neural network. On the basis of summarizing the research status of turn-to-turn insulation-related problems, this method studies the switching overvoltage generated in the process of breaking the dry-type air core reactor, the deterioration law of turn-to-turn insulation under the cumulative action of switching overvoltage, the influence of thermal aging on the Switching Overvoltage Withstand characteristics of turn-to-turn insulation, and the electrical aging life of turn-to-turn insulation under the power frequency overvoltage. Based on the deep neural network, the electrical aging life model of turn-to-turn insulation of the dry-type air core reactor under power frequency overvoltage is obtained. The results are as follows: with the increase of the applied voltage amplitude, the deterioration speed of the turn-to-turn insulation of the model sample accelerates. When the applied voltage amplitude reaches a certain value, the maximum discharge amount and pulse discharge power of the partial discharge pulse increase rapidly, and the image coincidence degree reaches 85%. The electric aging life curve of the modified interturn insulation model sample of the dry-type air core reactor has a high correlation with the measured aging life data, and the performance is more than 95%. The research results of this paper lay a practical foundation for further research on the deterioration mechanism of interturn insulation under the combined action of multiple factors and provide theoretical support for the risk and life assessment of the dry-type air core reactor.

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Section: Simulation Of Startingmentioning

confidence: 99%

Life Prediction of Dry Reactor Sensor Based on Deep Neural Network

et al. 2022

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“…Dry-type transformers are widely utilized in power systems owing to their compact structure, reduced operational losses, safety, and reliability [1,2]. Although many high-performance intelligent insulation materials have been developed and extensively employed [3,4], defects will still arise in dry-type transformers during their operation [5,6].…”

Section: Introductionmentioning

confidence: 99%

Localization of mechanical and electrical defects in dry-type transformers using an optimized acoustic imaging approach

Zhang,

Wang,

et al. 2023

PLoS ONE

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This paper presents an acoustic imaging localization system designed to pinpoint common defects in dry-type transformers by analyzing the unique sounds they produce during operation. The system includes an optimized microphone array and an improved multiple signal classification algorithm. Sound signal characteristics of typical defects, such as foreign object intrusion, screw loosening, and partial discharge, are investigated. A 64-element, 8-arm spiral microphone array is designed using a particle swarm optimization algorithm. The multiple signal classification algorithm enhances acoustic imaging quality in field environments by transforming the input from time-domain to preprocessed frequency-domain signals. The power spectra of subarray and main array are combined, forming the optimization algorithm’s output. Experimental results demonstrate the system’s effectiveness and accuracy.

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“…Literatürdeki araştırmaların çoğunun transformatörlerin genel olarak ağırlık ve maliyetini düşürmeye yönelik olduğu ve bu amaç doğrultusunda farklı tasarımlar gerçekleştirildiği ve farklı sezgisel algoritmalar kullanıldığı görülmüştür. Çalışmaların çoğunda genellikle farklı optimizasyon yöntemleri kullanılmış olsa da genel olarak optimizasyon parametreleri akım yoğunluğu ve demir kesit uygunluk faktörü olarak seçilmiştir [2], [5], [6], [7], [10], [15], [16], [17]. Bazı çalışmalarda ise bu parametrelerle beraber transformatör tasarım parametreleri yağlı ve kuru tip transformatör için değerlendirilerek transformatör ağırlıkları karşılaştırılmıştır [25].…”

Section: Introductionunclassified

Ateş Böceği Algoritması ile Yağlı Tip Transformatörün Ağırlık Optimizasyonu

AKDAĞ

ÇELEBİ

2022

DÜMF MD

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Efficiency and Cost Based Multi-optimization and Thermal/Electromagnetic Analyses of 3-Phase Dry-Type Transformer

Cited by 13 publications

References 18 publications

Life Prediction of Dry Reactor Sensor Based on Deep Neural Network

Life Prediction of Dry Reactor Sensor Based on Deep Neural Network

Localization of mechanical and electrical defects in dry-type transformers using an optimized acoustic imaging approach

Ateş Böceği Algoritması ile Yağlı Tip Transformatörün Ağırlık Optimizasyonu

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