Hassan Shanechi
- Teaching Professor of Electrical and Computer Engineering
Education
Ph.D. in System Science and Electrical Engineering, Michigan State University, 1980
B.S. and M.S., EE, Tehran University, Tehran, Iran, 1975
Research Interests
Hassan Shanechi joined the Department of Electrical and Computer Engineering at Illinois Institute of Technology in August 2007. His general area of research is nonlinear and intelligent systems. He has been especially active in the area of power system dynamics and security. He has done extensive research in analyzing stressed power systems and explaining their behavior when heavily loaded. He has also done research in power system planning and maintenance scheduling.
Publications
R. Shahnazi, H. Shanechi, and N. Pariz , 鈥淧osition Control of Induction and DC Servomotors: A Novel Adaptive Fuzzy PI Sliding Mode Control鈥, IEEE Transactions on Energy Conversion, to appear.
M. Oloomi Buygi, H. Shanechi, G. Balzer, M. Shahidehpour, and N. Pariz 鈥淣etwork Planning in Unbundled Power Systems鈥, IEEE Transactions on Power Systems, August 2006
M. Eidiani and H. Shanechi, 鈥淔AD-ATC: A new method for computing dynamic ATC鈥, Journal of Electrical Power & Energy Systems, # 28, February 2006
M. Oloomi Buygi, G. Balzer, H. Shanechi, and M. Shahidehpour, 鈥淢arket Based Transmission Expansion Planning鈥, IEEE Transactions on Power Systems, November 2004.
H. Shanechi, N. Pariz, and E. Vaahedi, 鈥淕eneral Nonlinear Modal Representation of Large Scale Power Systems鈥, IEEE Transactions on Power Systems, August 2003.
H. R. Mashhadi, H. Shanechi, and Caro Lucas, 鈥淎 New Genetic Algorithm with Lamarckian Individual Learning for Generation Scheduling鈥, IEEE Transactions on Power Systems, August 2003.
N. Pariz, H. Shanechi, and E. Vaahedi, 鈥淓xplaining and Validating Stressed Power Systems Behavior Using Modal Series鈥, IEEE Transactions on Power Systems, May 2003.
Expertise
Nonlinear and intelligent systems, power system dynamics and security, analyzing stressed power systems and explaining their behavior when heavily loaded, power system planning and maintenance scheduling.
