Impact of load ramping on power transformer dissolved gas analysis
- Cui, Huize, Yang, Liuging, Li, Shengtao, Qu, Guanghao, Wang, Hao, Abu-Siada, Ahmed, Islam, Syed
- Authors: Cui, Huize , Yang, Liuging , Li, Shengtao , Qu, Guanghao , Wang, Hao , Abu-Siada, Ahmed , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 170343-170351
- Full Text:
- Reviewed:
- Description: Dissolved gas in oil analysis (DGA) is one of the most reliable condition monitoring techniques, which is currently used by the industry to detect incipient faults within the power transformers. While the technique is well matured since the development of various offline and online measurement techniques along with various interpretation methods, no much attention was given so far to the oil sampling time and its correlation with the transformer loading. A power transformer loading is subject to continuous daily and seasonal variations, which is expected to increase with the increased penetration level of renewable energy sources of intermittent characteristics, such as photovoltaic (PV) and wind energy into the current electricity grids. Generating unit transformers also undergoes similar loading variations to follow the demand, particularly in the new electricity market. As such, the insulation system within the power transformers is expected to exhibit operating temperature variations due to the continuous ramping up and down of the generation and load. If the oil is sampled for the DGA measurement during such ramping cycles, results will not be accurate, and a fault may be reported due to a gas evolution resulting from such temporarily loading variation. This paper is aimed at correlating the generation and load ramping with the DGA measurements through extensive experimental analyses. The results reveal a strong correlation between the sampling time and the generation/load ramping. The experimental results show the effect of load variations on the gas generation and demonstrate the vulnerabilities of misinterpretation of transformer faults resulting from temporary gas evolution. To achieve accurate DGA, transformer loading profile during oil sampling for the DGA measurement should be available. Based on the initial investigation in this paper, the more accurate DGA results can be achieved after a ramping down cycle of the load. This sampling time could be defined as an optimum oil sampling time for transformer DGA.
- Authors: Cui, Huize , Yang, Liuging , Li, Shengtao , Qu, Guanghao , Wang, Hao , Abu-Siada, Ahmed , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 170343-170351
- Full Text:
- Reviewed:
- Description: Dissolved gas in oil analysis (DGA) is one of the most reliable condition monitoring techniques, which is currently used by the industry to detect incipient faults within the power transformers. While the technique is well matured since the development of various offline and online measurement techniques along with various interpretation methods, no much attention was given so far to the oil sampling time and its correlation with the transformer loading. A power transformer loading is subject to continuous daily and seasonal variations, which is expected to increase with the increased penetration level of renewable energy sources of intermittent characteristics, such as photovoltaic (PV) and wind energy into the current electricity grids. Generating unit transformers also undergoes similar loading variations to follow the demand, particularly in the new electricity market. As such, the insulation system within the power transformers is expected to exhibit operating temperature variations due to the continuous ramping up and down of the generation and load. If the oil is sampled for the DGA measurement during such ramping cycles, results will not be accurate, and a fault may be reported due to a gas evolution resulting from such temporarily loading variation. This paper is aimed at correlating the generation and load ramping with the DGA measurements through extensive experimental analyses. The results reveal a strong correlation between the sampling time and the generation/load ramping. The experimental results show the effect of load variations on the gas generation and demonstrate the vulnerabilities of misinterpretation of transformer faults resulting from temporary gas evolution. To achieve accurate DGA, transformer loading profile during oil sampling for the DGA measurement should be available. Based on the initial investigation in this paper, the more accurate DGA results can be achieved after a ramping down cycle of the load. This sampling time could be defined as an optimum oil sampling time for transformer DGA.
Online transformer internal fault detection based on instantaneous voltage and current measurements considering impact of harmonics
- Masoum, Ali, Hashemnia, Seyednaser, Abu-Siada, Ahmed, Masoum, Mohammad Sherkat, Islam, Syed
- Authors: Masoum, Ali , Hashemnia, Seyednaser , Abu-Siada, Ahmed , Masoum, Mohammad Sherkat , Islam, Syed
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Transactions on Power Delivery Vol. 32, no. 2 (2017), p. 587-598
- Full Text:
- Reviewed:
- Description: This paper investigates the performance of a recently proposed online transformer internal fault detection technique and examines impact of harmonics through detailed nonlinear simulation of a transformer using three-dimensional finite element modelling. The proposed online technique is based on considering the correlation between the instantaneous input and output voltage difference (ΔV) and the input current of a particular phase as a finger print of the transformer that could be measured every cycle to identify any incipient mechanical deformation within power transformers. To precisely emulate real transformer operation under various winding mechanical deformations, a detailed three-dimensional finite-element model is developed. Detailed simulations with (non)sinusoidal excitation are performed and analysed to demonstrate the unique impact of each fault on the ΔV-I locus. Impact of harmonic order, magnitude and phase angle is also investigated. Furthermore, practical measurements have been performed to validate the effect of winding short circuit fault on the proposed ΔV-I locus without and with the impact of system harmonics.
- Authors: Masoum, Ali , Hashemnia, Seyednaser , Abu-Siada, Ahmed , Masoum, Mohammad Sherkat , Islam, Syed
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Transactions on Power Delivery Vol. 32, no. 2 (2017), p. 587-598
- Full Text:
- Reviewed:
- Description: This paper investigates the performance of a recently proposed online transformer internal fault detection technique and examines impact of harmonics through detailed nonlinear simulation of a transformer using three-dimensional finite element modelling. The proposed online technique is based on considering the correlation between the instantaneous input and output voltage difference (ΔV) and the input current of a particular phase as a finger print of the transformer that could be measured every cycle to identify any incipient mechanical deformation within power transformers. To precisely emulate real transformer operation under various winding mechanical deformations, a detailed three-dimensional finite-element model is developed. Detailed simulations with (non)sinusoidal excitation are performed and analysed to demonstrate the unique impact of each fault on the ΔV-I locus. Impact of harmonic order, magnitude and phase angle is also investigated. Furthermore, practical measurements have been performed to validate the effect of winding short circuit fault on the proposed ΔV-I locus without and with the impact of system harmonics.
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