Development and Optimization of Methods for Objective Interpretation of FRA Test Results

• Applicant: Professor Dr.-Ing. Stefan Tenbohlen
• Subject Area: Electrical Energy Systems, Power Management, Power Electronics, Electrical Machines and Drives
• Term: from 2017 to 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 380135324

• Final Report Year: 2021

Final Report Abstract

No abstract available

Publications

• “A New Approach for High- Frequency Modelling of Disc Windings”. 2018 CIGRE session Paris, paper no. A2-214
  S. Tenbohlen, M. Tahir, E. Rahimpour, B. Poulin, S. Miyazaki
  
• “A Comprehensive Analysis of Windings Electrical and Mechanical Faults Using a High-Frequency Model,” Energies, vol. 13, no. 1, p. 105, Dec. 2019
  M. Tahir and S. Tenbohlen
  (See online at https://doi.org/10.3390/en13010105)
• „Influence of Employing Different Measuring Systems on Measurement Repeatability in Frequency Response Analysis of Power Transformers. IEEE Transactions on DEI, Vol. 35, Issue 2, April 2019, pp. 27-33
  S. Miyazaki, Y. Mizutani, M. Tahir, S. Tenbohlen
  (See online at https://doi.org/10.1109/mei.2019.8636103)
• “FRA lookup charts for the quantitative determination of winding axial displacement fault in power transformers,” in IET Electric Power Applications, vol. 14, Issue 12, December 2020, p. 2370 – 2377
  Mehran Tahir and Stefan Tenbohlen
  (See online at https://doi.org/10.1049/iet-epa.2020.0273)
• "Analysis of Statistical Methods for Assessment of Power Transformer Frequency Response Measurements," in IEEE Transactions on Power Delivery, vol. 36, no. 2, pp. 618-626, April 2021
  M. Tahir, S. Tenbohlen and S. Miyazaki
  (See online at https://doi.org/10.1109/tpwrd.2020.2987205)
• “Transformer Winding Condition Assessment Using Feedforward Artificial Neural Network and Frequency Response Measurements" Energies 14, no. 11: 2021
  M. Tahir, S. Tenbohlen
  (See online at https://doi.org/10.3390/en14113227)