ExpertiseSmart power grid, renewable energy, cyber-physical resilience, data analytics
Smart power grids and renewable energy systems: modeling, situational awareness, cyber-physical resilience, and machine learning applications
- Ph D: Electrical Engineering, Northeastern University - Boston, MA
Dissertation/Thesis Title: Reliable and Efficient Methods for Identification of Parameter and Measurement Errors in Power Networks
- MS: Electrical Engineering, Tsinghua University - Beijing, China
Dissertation/Thesis Title: Comprehensive Voltage Stability Assessment Incorporating Wind Power
- BS: Electrical Engineering, Tsinghua University - Beijing, China
BiosketchYuzhang Lin, Ph.D., is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts, Lowell. He obtained his Ph.D. degree from Northeastern University, Boston, MA, and his B.Eng. and M.S. degrees from Tsinghua University, Beijing, China.
His research interests focus on smart grid and renewable energy, especially in the aspects of modeling, situational awareness, cyber-physical resilience, and machine learning applications. He publishes widely in the top journals of the domain, and also serves as an Editor/Reviewer for many of these journals. He serves as the Co-Chair of the IEEE PES Task Force for Standard Test Cases for Power Systems State Estimation. He is a recipient of the prestigious Graduate Student Outstanding Research Award at Northeastern University, Boston, MA. His research is funded by NSF, DOE, and ONR. He is a recipient of NSF CAREER Award.
Selected Awards and Honors
- NSF CAREER Award (2022), National Science Foundation.
- Graduate Student Outstanding Research Award (2018), Northeastern University.
- Cheng, G., Lin, Y., Chen, Y., and Bi., T. (2021). Adaptive state estimation for power systems measured by PMUs with unknown and time-varying error statistics. IEEE Transactions on Power Systems, 36(5), 4482-4491.
- Edib, S. N., Lin, Y., Vokkarane, V. M., Qiu, F., Yao, R., and Zhao, D. (2021). Optimal PMU restoration for power system observability recovery after massive attacks. IEEE Transactions on Smart Grid, 12(2), 1565-1576.
- Fang, Z., Lin, Y., Song, S., Li, C., Lin, X., and Chen, Y. (2021). State estimation for situational awareness of active distribution system with photovoltaic power plants. IEEE Transactions on Smart Grid, 12(1), 239-250.
- S. Hassan, O. Sale, K. Alnasser, N. Hurley,, ., H. Zhang, U. Philipose,, ., Lin, Y. (2019). Broadband light-matter interaction due to resonance cavities in graded photonic super-crystals. OSA Continuum,2(11) 3272--3280.
- Lin, Y., and Abur, A. (2018). A highly efficient bad data identification approach for very large scale power systems. IEEE Transactions on Power Systems, 33(6), 5979-5989.
- Lin, Y., and Abur, A. (2018). A new framework for detection and identification of network parameter errors. IEEE Transactions on Smart Grid, 9(3), 1698-1706.
- “Cyber-Physically Resilient Situational Awareness of Power Grids,” Panel Session: Evolutionary Grid Communication Planning and Applications in 5G Era and Future - IEEE Innovative Smart Grid Technologies (ISGT) Conference, New Orleans, Louisiana, USA - Apr 2022.
Selected Intellectual Property
- Abur, A., and Lin, Y. “Techniques for Processing Power System Network Information,” U.S. patent 11,176,289 B2, Nov. 16, 2021.