Assosiate Professor

Phone No: +98 21 84062413

Email: a.razi.kazemi@kntu.ac.ir

Personal website: http://wp.kntu.ac.ir/razi.kazemi

Education:

      Ph.D.: Electrical engineering -Power System, Sharif University of Technology, Tehran, Iran, 2013.

       M.Sc.: Electrical engineering -Power System, Tehran University, Tehran, Iran, 2010.

       B.Sc.: Electrical engineering, K.N. Toosi University of Technology, Tehran, Iran, 2008.

 

Research Interest:

• Circuit Breakers On-Line Monitoring
• High Power Technology
• Pulsed Power Technology
• Reliability Centered-Maintenance
• Condition-Based Maintenance
• Asset Management
• Transients in Power System
• Insulation Coordination

Biography:

Ali A. Razi-Kazemi received the B.Sc. and M.Sc. degree in Electrical engineering from K.N. Toosi University of Technology and Tehran University, Tehran, Iran, respectively, and a Ph.D. degree in Electrical Engineering from the Sharif University of Technology, Iran and Research Attachment at Aalto University, Espoo, Finland, in 2013. Dr. Razi-Kazemi is the Assistant Professor in the Department of Electrical Engineering at K.N. Toosi University of Technology. His research interests include high power technology, reliability- and condition-based maintenance, asset management, and insulation coordination.

Selected journal papers:

1. Bagherpoor, A., Rahimi-Pordanjani, S., Razi-Kazemi, A.A., Niayesh, K., “Online condition assessment of interruption chamber of gas circuit breakers using arc voltage measurement,” IEEE Transactions on Power Delivery, 2017.
2. Ariannik, M., Razi-Kazemi, A.A., Lehtonen, M., “Effect of cumulative moisture content on the degradation of transformer paper insulation,” IEEE Transactions on Dielectrics and Electrical Insulation, 2017.
3. Razi-Kazemi, A.A., “Circuit breaker condition assessment through a fuzzy-probabilistic analysis of actuating coil’s current,” IET Generation, Transmission, and Distribution, 2016.
4. Razi-Kazemi, A.A., “Applicability of auxiliary contacts in circuit breaker online condition assessment,” Electric Power Systems Research, 2015.
5. Razi-Kazemi, A.A., Vakilian, M., Niayesh, K., Lehtonen, M., “Data mining of online diagnosed waveforms for probabilistic condition assessment of SF6 circuit breakers,” IEEE Transactions on Power Delivery, 2015.