Dynamic Thermal Model for Power Transformers

Aslam, Muhammad; Haq, Inzamam ul; Rehan, Muhammad; Basit, Abdul; Arif, Muhammad; Khan, M.I.; Sadiq, Muhammad; Arbab, Muhammad Naeem

doi:10.1109/access.2021.3078759

Cited by 13 publications

(4 citation statements)

References 22 publications

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“…As the transformer life mainly depends on the condition of insulation; the deterioration of insulation can be regarded as a key factor for complete failure of the transformer in practice. PD activity is electrical in nature, but is accompanied by thermal effects that are mainly responsible for insulation degradation ultimately leading to breakdown [29,30].…”

Section: A Partial Discharge Activitymentioning

confidence: 99%

Prognostication of Failures Using Signal-to-Noise Ratio to Determine Partial Discharges Activities in Power Transformers

et al. 2022

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The increase in number of power transformer necessitates increased awareness among power system engineers to monitor transformer health in order to avoid complete failures that may results in prolonged outages. The utilities, nowadays, are exploring different ways of detecting these faults in an early stage. This paper aims to present a real-time monitoring technique for a three-phase transformer using data analytics. Accordingly, the use of signal to noise ratio (SNR) for fault detection in power transformers has been described. This technique determines the partial discharge with the help of sensors needed for unique identification of failed transformers in different test systems. The SNR for different transformer coils installed in field conditions has been compared and discussed in detail. The technique is expected to enable power transformer operators for detection of incipient faults and thus can avoid catastrophic failures and the resultant losses.INDEX TERMS Incipient Faults, Partial discharges, Signal-to-Noise Ratio, Transformer health.

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Section: A Partial Discharge Activitymentioning

confidence: 99%

Prognostication of Failures Using Signal-to-Noise Ratio to Determine Partial Discharges Activities in Power Transformers

et al. 2022

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“…Current research on transformer hotspot temperatures primarily focuses on computational methodologies. On the one hand, 2D or simpler 3D models [12][13][14], along with tools like Simulink, are utilized to establish the electrothermal equivalent models [15] for calculating hotspot temperature. Comparisons between 2D and 3D modeling approaches have revealed significant inaccuracies associated with 2D models [16].…”

Section: Introductionmentioning

confidence: 99%

Full-Scale Modeling and FBGs Experimental Measurements for Thermal Analysis of Converter Transformer

Yang,

Gao,

Wang

et al. 2024

Sensors

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As the imbalance between power demand and load capacity in electrical systems becomes increasingly severe, investigating the temperature variations in transformers under different load stresses is crucial for ensuring their safe operation. The thermal analysis of converter transformers poses challenges due to the complexity of model construction. This paper develops a full-scale model of a converter transformer using a multi-core high-performance computer and explores its thermal state at 80%, 100%, and 120% loading ratios using the COUPLED iteration method. Additionally, to validate the simulation model, 24 FBGs are installed in the experimental transformer to record the temperature data. The results indicate a general upward trend in winding the temperature from bottom to top. However, an internal temperature rise followed by a decrease is observed within certain sections. Moreover, as the loading ratio increases, both the peak temperature and temperature differential of the transformer windings rise, reaching a peak temperature of 107.9 °C at a 120% loading ratio. The maximum discrepancy between the simulation and experimental results does not exceed 3.5%, providing effective guidance for the transformer design and operational maintenance.

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“…Additionally, this method is not practical for transformers with built-in transformers. The optimal position of the sensor and the exact location of the hot spot are also problems with direct measurement [21]- [23]. Statistical approach is another method which determined by calculating the transformer internal temperature.…”

Section: Introductionmentioning

confidence: 99%

Online Estimation of Transformer Hot Spot Temperature by Considering the Effects of Load Profile Modeling

Moosavi,

Mokhtari

2023

Scientia Iranica

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One of the most valuable components in power systems is power transformer whose failure may result in a significant power loss. Therefore, one of the critical issues in power transformer operation is its health monitoring. Moreover, it was shown that the aging rate of transformers is very sensitive to the hot spot temperature, and when this temperature exceeds a threshold value, the aging rate increases. Given the fact that using temperature sensors in prefabricated and built-in transformers is not practical, thermal models are used to estimate transformer hot spot temperature. Since the transformer hot spot temperature is a key factor in the condition monitoring of a transformer, and in case it will exceed a threshold value, preventive actions should be taken in the proposed algorithm, the sensitivity of this important parameter with respect to the load profile sampling time is investigated. This paper proposes a fast online algorithm for the estimation of power transformer hot spot temperature by reducing the number of calculations without sacrificing accuracy. The proposed algorithm is applied to a 250 MVA transformer using MATLAB software. The results were compared with the actual factory test results and the efficiency of the proposed algorithm was shown.

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Dynamic Thermal Model for Power Transformers

Cited by 13 publications

References 22 publications

Prognostication of Failures Using Signal-to-Noise Ratio to Determine Partial Discharges Activities in Power Transformers

Prognostication of Failures Using Signal-to-Noise Ratio to Determine Partial Discharges Activities in Power Transformers

Full-Scale Modeling and FBGs Experimental Measurements for Thermal Analysis of Converter Transformer

Online Estimation of Transformer Hot Spot Temperature by Considering the Effects of Load Profile Modeling

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