Transformer Condition Monitoring is the process of data acquisition and processing associated with various transformer parameters so as to predict and prevent the failure of the transformer. This is done by observing the transformer parameter deviation from the expected value. Transformer is the most important asset of power transmission and distribution system. Damage to the transformer may cause power outages, personal and environmental hazards and expensive re-routing or power purchases from other suppliers. Damage to the transformer may occur due to various causes. Interruptions and in-room transformer failures are usually generated from dielectric breakage, distortion winding caused by short circuit retaining, winding and magnetic circuit hot spots, power failures, insulation damage, lightning, inadequate maintenance, loose connections, overload, accessories failure such as OLTC, bushing, etc. [1] Integrating monitoring of 'individual cause' makes it possible to monitor the overall condition of the transformer. An important aspect of monitoring transformer conditions is [2]
- Thermal Modeling
- Dissolved Gas Analysis
- Frequency Response Analysis
- Partial Decay Analysis
Video Condition monitoring of transformers
Pemodelan Termal
The transformer benefit period is determined partially by the ability of the transformer to remove the heat generated internally into its environment [3]. Comparison of actual and predicted operating temperatures can provide a diagnosis of sensitive condition of the transformer and may indicate abnormal operation. The consequences of rising temperatures may not be sudden, but gradually as long as it is within the lower limit. Among these consequences, deterioration of insulation is economically important. Isolation becomes very expensive, the damage is undesirable. Thermal modeling is the development of mathematical models that predict the temperature profiles of power transformers using thermal analysis principles. The thermal model is used to determine the upper oil temperature and the hot spot temperature (maximum temperature occurring in the winding insulation system) temperature rise
Maps Condition monitoring of transformers
Dissolved Gas Analysis
The gas is produced by transformer oil degradation and solid insulating material. The gas is generated at a much faster rate each time an electric error occurs [4]. The normal causes of the error gases are classified into three categories: Corona or partial discharge, thermal heating and arch. These errors can be detected by evaluating the quantity of hydrocarbon gas, hydrogen and carbon oxides present in the transformer. Different gases can serve as markers for different types of errors. Individual gas concentrations and relationships allow predictions of whether errors have occurred and what types might occur [5].
Frequency Response Analysis
When the transformer is subjected to high currents through the fault current, the mechanical structure and winding are subjected to severe mechanical stresses resulting in twisting and deformation motions. This can also cause damage to insulation and rotary-to-play error [6]. Frequency response analysis (FRA) is a highly intrusive sensitive technique for detecting errors of winding motion and deformation assessment caused by loss of clamping pressure or by short circuit strength. The FRA technique involves measuring the impedance of a transformer winding with a low voltage sine input varying in a wide frequency range [7].
Partial Decay Analysis
Partial discharge (PD) occurs when the local electric field exceeds the threshold value, resulting in partial damage of the surrounding medium. Its cumulative effect causes insulation degradation [8]. PD is initiated by a defect during manufacture, or a higher pressure option dictated by design considerations. Measurements can be collected to detect this PD and monitor the health of the insulation. The PDs manifests as a sharp current pulse at the transformer terminal, which depends on the type of insulation, defect, measurement circuit and detector used [9].
References
- [1] Arvind Dhingra, Singh Khushdeep and Kumar Deepak, "Monitoring power transformer conditions: Reviews." Conference and Exposition Transmission and Distribution, 2008. Q & amp; D. IEEE/PES. IEEE, 2008.
- [2] W. H. Tang and Q. H. Wu, "Surveillance of Conditions and Assessment of Power Transformators Using Computational Intelligence", Springer, 2011
- [3] Tang, W. H., Q. H. Wu, and Z. J. Richardson. "Thermally based thermal power transformer circuit model." Electric Power Applications, IEE Proceedings-. Vol. 149. No. 2. IET, 2002.
- [4] Emsley, A. M., and G. C. Stevens. "Review of chemical indicator degradation of insulation of cellulosic paper in an oil-filled transformer." Science, Measurement and Technology, IEE Proceedings-. Vol. 141. No. 5. IET, 1994.
- [5] Wang, Dian. Diagnosis of ontology-based errors for power transformers. Diss. University of Liverpool, 2011.
- [6] Abu-Elanien, Ahmed EB, and M. M. Salama. "Survey on monitoring transformer conditions." Power Engineering, 2007 Great Engineering System Conference. IEEE, 2007.
- [7] Gonzalez, Carlos, et al. "The transformer diagnostic approach uses the method of frequency response analysis." IEEE Industrial Electronics, IECON 2006-32nd Annual Conference on. IEEE, 2006.
- [8] Bartnikas, R. "Partial discharge, their mechanism, detection and measurement." Dielectric and Electrical Insulation, IEEE Transactions in 9.5 (2002): 763-808.
- [9] Stone, G. C., et al. "The practical implementation of the ultrawideband partial detachment detector." Electrical Insulation, IEEE Transactions on 27.1 (1992): 70-81.
- (10) Giesecke, J.L. Assessment of Transformer Conditions using HFCT method. see article on transformers-magazine.com July 2016
Source of the article : Wikipedia
0 Comments