David Lubkeman

Electrical and Computer Engineering

  • Phone: 919.513.2024
  • Office: 100-21 Keystone Science Center

David Lubkeman has more than 25 years of experience in distribution systems and automation and has been an active participant in technical development activities, resulting in more than 40 publications and 13 US patents. His previous industry experience includes working at Sensus as a senior product manager for distribution automation; at KEMA consulting in the areas of smart grid business case analysis, large-scale energy storage and renewable energy integration; and at ABB, where he was involved in the development of solutions for distribution automation and asset management. Lubkeman’s prior academic experience was as an associate professor in the Holcombe Department of Electrical and Computer Engineering at Clemson University. He is also a licensed professional engineer.

Research Interests

Lubkeman’s research focuses on the area of power systems engineering. He leads the Electrical Power Systems Engineering (EPSE) Master of Science professional degree program. He also is a research faculty member associated with the NSF FREEDM Systems Center.

Education

DegreeProgramSchoolYear
Ph.D.Doctor of Philosophy in Electrical EngineeringPurdue University1983
MSEEMaster of Science in Electrical EngineeringPurdue University
BSEEBachelor of Science in Electrical EngineeringPurdue University

Honors and Awards

  • 2015 | Fellow, IEEE

Discover more about David Lubkeman

 

Publications

Under-Frequency Load Shedding for Power Reserve Management in Islanded Microgrids
Xu, B., Paduani, V. D., Xiao, Q., Song, L., Lubkeman, D., & Lu, N. (2024), IEEE TRANSACTIONS ON SMART GRID, 15(5), 4662–4673. https://doi.org/10.1109/TSG.2024.3393426
A Secure and Adaptive Hierarchical Multi-Timescale Framework for Resilient Load Restoration Using a Community Microgrid
Shirsat, A., Muthukaruppan, V., Hu, R., Paduani, V. D., Xu, B., Song, L., … Tang, W. (2023), IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 14(2), 1057–1075. https://doi.org/10.1109/TSTE.2023.3251099
A Data-driven Pivot-point-based Time-series Feeder Load Disaggregation Method
Wang, J., Zhu, X., Liang, M., Meng, Y., Kling, A., Lubkeman, D., & Lu, N. (2021), 2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM). https://doi.org/10.1109/PESGM46819.2021.9638034
A Load Switching Group based Feeder-level Microgrid Energy Management Algorithm for Service Restoration in Power Distribution System
Hu, R., Li, Y., Zhang, S., Shirsat, A., Muthukaruppan, V., Tang, W., … Lu, N. (2021), 2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM). https://doi.org/10.1109/PESGM46819.2021.9638231
Agent-Based Modeling of Feeder-Level Electric Vehicle Diffusion for Distribution Planning
Sun, L., & Lubkeman, D. (2021), 2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM). https://doi.org/10.1109/PESGM46819.2021.9638119
FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets
Liang, M., Meng, Y., Wang, J., Lubkeman, D., & Lu, N. (2021), 2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM). https://doi.org/10.1109/PESGM46819.2021.9638247
Hierarchical Multi-timescale Framework For Operation of Dynamic Community Microgrid
Shirsat, A., Muthukaruppan, V., Hu, R., Lu, N., Baran, M., Lubkeman, D., & Tang, W. (2021), 2021 IEEE POWER & ENERGY SOCIETY GENERAL MEETING (PESGM). https://doi.org/10.1109/PESGM46819.2021.9638104
Secondary Voltage and Frequency Regulation for Grid Re-Synchronization in Microgrid with Unified Virtual Oscillator Controlled Multi-port Converters
Bipu, M. R. H., Awal, M. A., Cen, S., Zabin, S., Khan, M., Lubkeman, D., & Husain, I. (2021), 2021 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE), pp. 900–905. https://doi.org/10.1109/ECCE47101.2021.9595901
Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm
Long, Q., Yu, H., Xie, F., Lu, N., & Lubkeman, D. (2021), IEEE TRANSACTIONS ON SMART GRID, 12(2), 943–952. https://doi.org/10.1109/TSG.2020.3026617
FeederGAN: Synthetic Feeder Generation via Deep Graph Adversarial Nets
Liang, M., Meng, Y., Wang, J., Lubkeman, D. L., & Lu, N. (2021), IEEE TRANSACTIONS ON SMART GRID, 12(2), 1163–1173. https://doi.org/10.1109/TSG.2020.3025259

View all publications via NC State Libraries

David Lubkeman