Mohammad Reza Khalghani

Assistant Professor

Office Location
Innovation, Science, and Technology Building, 4700 Research Way, Room 2100, Lakeland, FL 33805

 

Education
Ph.D. in Electrical Engineering, West Virginia University, 2019
M.S. in Electrical Engineering, University of Birjand, 2012

 

Social Media Accounts/Websites*
Google Scholar Profile
LinkedIn

 

About
Dr. Mohammad Reza Khalghani joined Florida Polytechnic University as an assistant professor in the department of electrical and computer engineering in August 2019. His research interests are in the areas of smart grid, cyber-security, renewable energy, control theories and application, and electric vehicle integration. In his Ph.D. program at West Virginia University, he mainly focused on designing resilient control of microgrids against cyber disruption and renewable energy intermittency, designing artificial intelligence techniques, and stochastic modeling of power systems. He serves as a reviewer for high-impact ISI journals such as IEEE Transaction on Vehicular Technology, Journal of Applied Energy, International Journal of Power and Energy Systems, Journal of Neural Computing and Applications, Journal Sustainable Cities and Society, Optimal Control, Applications and Methods, and International Journal of Hydrogen Energy.

 

Expertise

  • Smart Grid
  • Renewable Energy
  • Cyber-Security
  • Control Theories and Application
  • Electric Vehicle Integration

 

Professional Activities

  • Member, IEEE
  • Member, IEEE Power & Energy Society

 

Selected Publications

  • M. R. Khalghani, S. K. Solanki, J. Solanki, and A. Sargolzaei, Resilient and stochastic load frequency control of microgrids,” in 2019 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2019, pp. 1-5.
  • M. R. Khalghani, S. Khushalani-Solanki, J. Solanki, and A. Sargolzaei, Stochastic load frequency control of microgrids including wind source based on identification method,” in Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEICI&CPS Europe), 2018 IEEE International Conference on. IEEE, 2018, pp. 1-6.
  • M. R. Khalghani, M. H. Khooban, E. Mahboubi-Moghaddam, N. Vafamand, and M. Goodarzi, \A self-tuning load frequency control strategy for microgrids: Human brain emotional learning,” International Journal of Electrical Power Energy Systems, vol. 75, pp. 311-319, 2016.
  • H. Heydari-Doostabad, M. R. Khalghani, M. H. Khooban, “A Novel Control System Design to Improve LVRT Capability of Fixed Speed Wind Turbines using STATCOM in Presence of Voltage Fault,” International Journal of Power and Energy Systems, Vol. 77, pp. 280-286, 2016.
  • M. R. Khalghani, and M.H. Khooban, “A Novel Self-Tuning Control Method Based on Regulated Bi-objective Emotional Learning Controller’s Structure with TLBO Algorithm  to Control DVR Compensator,” Journal of Applied Soft Computing, Vol. 24, pp. 912–922, November 2014.
  • M. R. Khalghani, and M.H. Khooban, “A Novel Self-Tuning Control Method Based on Regulated Bi-objective Emotional Learning Controller’s Structure with TLBO Algorithm  to Control DVR Compensator,” Journal of Applied Soft Computing, Vol. 24, pp. 912–922, November 2014.
  • M.R. Khalghani, M.A. Shamsi-nejad and M. H. Khooban,“DVR Control Using Bi-objective Optimization to Improve Power Quality’s Indices,” IET Science, Measurement & Technology, Vol. 8, Issue 4, pp. 203–213, July 2014.

 

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