David Lubkeman
Electrical and Computer Engineering
- Phone: 919.513.2024
- Email: dllubkem@ncsu.edu
- 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
| Degree | Program | School | Year |
|---|---|---|---|
| Ph.D. | Doctor of Philosophy in Electrical Engineering | Purdue University | 1983 |
| MSEE | Master of Science in Electrical Engineering | Purdue University | |
| BSEE | Bachelor of Science in Electrical Engineering | Purdue University |
Honors and Awards
- 2015 | Fellow, IEEE
Discover more about David Lubkeman
- FREEDM researchers receive funding for work on grid resilience tools
- Lubkeman and Rotenberg Elevated to IEEE Fellow
- Huang and Lubkeman Receive Award for Research by GridBridge
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
- 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., & 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
- 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
