Economic Analysis of Vegetable-Oil-Filled Power Transformers in Brazilian Energy Distribution Systems Compared to Mineral-Oil-Filled Ones

Almeida, Larissa Santos; Muniz, Pablo Rodrigues

doi:10.1007/s40313-021-00730-z

Cited by 5 publications

(2 citation statements)

References 7 publications

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“…Almeida and Muniz improved the zero-sequence power method and used the zero-sequence active power component to determine the fault segment, which was suitable for the arc suppression coil grounding system. However, the method was interfered by the unbalanced current of the current transformer, resulting in low reliability of fault location [4]. e transient zero-mode power direction method proposed by Bhatia is used to calculate the transient zero-mode voltage and current to determine the fault direction and then the field terminal measuring equipment is used to determine the fault section.…”

Section: Literature Reviewmentioning

confidence: 99%

Realization of Single-Phase Grounding Fault Location and Recovery Technology in Distribution Network

Zhang

Tang

Zhu

et al. 2022

International Transactions on Electrical Energy Systems

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In order to locate the single-phase-to-ground fault in distribution network, a research method of single-phase-to-ground fault location and recovery technology in distribution network is proposed. According to the characteristics of single-phase-to-ground fault in distribution network, the fault characteristics of zero-sequence current and three-phase current transient records are extracted by generalized S transform of correlation coefficient, and multi-source redundant information is formed. Fuzzy C-means clustering analysis method is used to fuse multiple fault features online location strategy. The simulation results show that the fuzzy clustering based on FCM changes continuously with the accumulation of samples, and the sample center changes with the enrichment of the samples. When the arc suppression coil is grounded with different initial phase angle transition resistance and intermittent fault, the state of each measuring point can be correctly identified, and the accurate energization rate is 97%. The test results show that the system can achieve accurate positioning for all sections.

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Section: Literature Reviewmentioning

confidence: 99%

Realization of Single-Phase Grounding Fault Location and Recovery Technology in Distribution Network

Zhang

Tang

Zhu

et al. 2022

International Transactions on Electrical Energy Systems

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“…The state quantity of uninterrupted power detection can not only reflect the overall state of the transformer from many aspects, but also an important basis for the analysis and diagnosis of the failure mode. Common body faults can be divided into four categories according to their parts: body insulation faults, winding connection faults, winding deformation faults and iron core faults; according to their nature, they can be divided into: thermal faults, electrical faults, deformation faults, moisture and dirt faults [7][8]. According to the information in the table, a simple analysis can be done: the sound frequency band range of bird song and corona discharge sound does not overlap with the sound frequency band range of the transformer body, so it is not necessary to consider it when denoising.…”

Section: Coarse Analysis Of Failure Modesmentioning

confidence: 99%

Voiceprint Feature Extraction of Large Power Transformers in Uninterrupted Diagnosis and Early Warning Technology

Wang¹,

Zhang²,

Zhang³

et al. 2022

J. Phys.: Conf. Ser.

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Condition-based maintenance is to select the most suitable maintenance method according to the real-time operating state of the converter. Transformer condition evaluation and fault diagnosis is an important basis for condition maintenance, and it is also the key to ensure the normal implementation of condition maintenance. The main purpose of this paper is to study the application of voiceprint feature extraction in large-scale power transformers in uninterruptible power failure diagnosis and early warning technology. In this paper, a comprehensive and in-depth study of the state quantity of transformer uninterrupted detection is carried out. Experiments show that when CR<0.10, the matrix is satisfactory and consistent, and the weight distribution is reasonable.

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Transformer fault diagnosis technology based on AdaBoost enhanced transferred convolutional neural network

Tao,

Sun,

Yang

et al. 2025

Expert Systems with Applications

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Economic Analysis of Vegetable-Oil-Filled Power Transformers in Brazilian Energy Distribution Systems Compared to Mineral-Oil-Filled Ones

Cited by 5 publications

References 7 publications

Realization of Single-Phase Grounding Fault Location and Recovery Technology in Distribution Network

Realization of Single-Phase Grounding Fault Location and Recovery Technology in Distribution Network

Voiceprint Feature Extraction of Large Power Transformers in Uninterrupted Diagnosis and Early Warning Technology

Transformer fault diagnosis technology based on AdaBoost enhanced transferred convolutional neural network

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