Xie, Le individual record
My research interest includes modeling and control of large-scale complex systems, smart grid applications in support of renewable energy integration, and electricity markets.
education and training
- Ph.D. in Electrical and Computer Engineering, Carnegie Mellon University - (Pittsburgh, Pennsylvania, United States) 2009
- M.S. in Engineering Sciences, Harvard University - (Cambridge, Massachusetts, United States) 2005
- B.E. in Electrical Engineering, Tsinghua University - (Beijing, Beijing, China) 2004
- Huang, T., Gao, S., & Xie, L. e. (2022). A Neural Lyapunov Approach to Transient Stability Assessment of Power Electronics-Interfaced Networked Microgrids. IEEE Transactions on Smart Grid. 13(1), 106-118.
- Zheng, X., Xu, N., Trinh, L., Wu, D., Huang, T., Sivaranjani, S., Liu, Y., & Xie, L. e. (2022). A multi-scale time-series dataset with benchmark for machine learning in decarbonized energy grids.. Sci Data. 9(1), 359.
- Geng, X., Xie, L. e., & Modarresi, M. S. (2022). Computing Essential Sets for Convex and Nonconvex Scenario Problems: Theory and Application. IEEE Transactions on Control of Network Systems. 9(1), 269-281.
- Wu, D., Zheng, X., Menati, A., Smith, L., Xia, B., Xu, Y., Singh, C., & Xie, L. e. (2022). How much demand flexibility could have spared texas from the 2021 outage?. Advances in Applied Energy. 7, 100106-100106.
- Xie, L. e., Zheng, X., Sun, Y., Huang, T., & Bruton, T. (2022). Massively Digitized Power Grid: Opportunities and Challenges of Use-Inspired AI. Proceedings of the IEEE. PP(99), 1-26.
- Zhang, L. u., Wang, B., Wu, D., Xie, L. e., Kumar, P. R., & Shi, W. (2019). Fast Electromagnetic Transient Simulation Based on Hierarchical Low-Rank Approximation. 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT). 00, 1-5.
- Gu, Y., Chen, Q., Liu, K., Xie, L. e., & Kang, C. (2019). GAN-based Model for Residential Load Generation Considering Typical Consumption Patterns. 2019 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT).
- Zhou, Y., & Xie, L. e. (2017). Detection of bad data in multi-area state estimation. 2017 IEEE Texas Power and Energy Conference (TPEC), 2017 IEEE Texas Power and Energy Conference (TPEC). 1-6.
- Modarresi, M. S., Huang, T., Ming, H., & Xie, L. e. (2017). Robust phase detection in distribution systems. 2017 IEEE Texas Power and Energy Conference (TPEC), 2017 IEEE Texas Power and Energy Conference (TPEC). 1-5.
- Ming, H., & Xie, L. e. (2016). Revenue adequacy of wholesale electricity markets with demand response providers. 2016 IEEE Power and Energy Society General Meeting (PESGM), 2016 IEEE Power and Energy Society General Meeting (PESGM). 2016-November, 1-5.
Repository Documents / Preprints1
- Wu, D., Zheng, X., Xu, Y., Olsen, D., Xia, B., Singh, C., & Xie, L. e. (2021). An Open-source Model for Simulation and Corrective Measure Assessment of the 2021 Texas Power Outage.
in the news
- Shifting costs: Rate plan would target consumers who strain power grid Research@Texas A&M July 19, 2021
- Using Solar Panels to Decontaminate Water Azo Cleantech November 5, 2020
- Water-Energy Nanogrid Provides Solution For Rural Communities Lacking Basic Amenities Texas A&M Today November 4, 2020
- Texas A&M University Announces 2020 EDGES Fellows Texas A&M Today October 7, 2020
- Smart Technology Improves Energy Supply in Homes Affected by Blackouts Azo Cleantech July 24, 2020
awards and honors
recent teaching activities
chaired theses and dissertations
- Wiseman, Benjamin Patrick (2018-12). Quantifying the Effect of Air Conditioning Dynamics on Power System Stability Limits. (Master's Thesis)
- Ming, Hao (2018-08). A Household-level Incentive-based Demand Response: Theory, Platform and Experiment. (Doctoral Dissertation)
- Zhou, Yuqi (2018-05). Multi-Area State Estimation in Adversarial Environment. (Master's Thesis)
- Clark, Angelica (2017-12). A Machine Learning Approach to Weak Grid Identification for Large Scale Electrical Power Systems. (Master's Thesis)
- Wu, Meng (2017-12). Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration. (Doctoral Dissertation)
Texas A&M University; Electrical Engineering; 3128 TAMU
College Station, TX 77843-3128