Getting Started
Quick Start Guide
Research Demo
- Disturbance Propagation in Power Grids With High Converter Penetration by Dr. Hantao Cui
- Transmission-and-Distribution Co-Simulation Framework by Dr. Xin Fang
- Electric Vehicles Charging Time Constrained Deliverable Provision of Secondary Frequency Regulation by Jinning Wang
- Virtual Inertia Scheduling (VIS) for Real-time Economic Dispatch by Buxin She
- Virtual Inertia Scheduling (VIS) for Microgrids with Static and Dynamic Security Constraints by Buxin She
Presentations and Talks
- DiME and AGVis: Distributed Messaging Environment and Geographical Visualizer for CURENT Large-scale Testbed (LTB) by Jinning Wang
- Advancing a Decarbonized Power Grid: A Transient Stability Perspective with LTB - Talk at UTK ECE522 Course by Jinning Wang
- CURENT Large-scale Testbed (LTB) - A Comprehensive Power System Testing Platform, Presentation at CURENT Industry Conference 2023 by Jinning Wang
- CURENT Large-scale Testbed (LTB), A seminar at Stanford in April 2021 by Dr. Fangxing (Fran) Li
Publications with LTB Support
Journal
- H. Cui et al., “Disturbance Propagation in Power Grids With High Converter Penetration,” in Proceedings of the IEEE, doi: 10.1109/JPROC.2022.3173813.
- J. Wang et al., “Electric Vehicles Charging Time Constrained Deliverable Provision of Secondary Frequency Regulation,” in IEEE Transactions on Smart Grid, doi: 10.1109/TSG.2024.3356948.
- B. She, F. Li, H. Cui, J. Wang, Q. Zhang and R. Bo, “Virtual Inertia Scheduling (VIS) for Real-time Economic Dispatch of IBRs-penetrated Power Systems,” in IEEE Transactions on Sustainable Energy, doi: 10.1109/TSTE.2023.3319307.
- J. Pei, J. Wang, Z. Wang and D. Shi, “Precise Recovery of Corrupted Synchrophasors Based on Autoregressive Bayesian Low-Rank Factorization and Adaptive K-Medoids Clustering,” in IEEE Transactions on Power Systems, vol. 38, no. 6, pp. 5834-5848, Nov. 2023, doi: 10.1109/TPWRS.2022.3221291.
- Zhang, Q., Li, F. A Dataset for Electricity Market Studies on Western and Northeastern Power Grids in the United States. Sci Data 10 , 646 (2023). doi: 10.1038/s41597-023-02448-w.
- W. Cui, W. Yang and B. Zhang, “A Frequency Domain Approach to Predict Power System Transients,” in IEEE Transactions on Power Systems, vol. 39, no. 1, pp. 465-477, Jan. 2024, doi: 10.1109/TPWRS.2023.3259960.
- N. Gao, D. W. Gao and X. Fang, “Manage Real-Time Power Imbalance With Renewable Energy: Fast Generation Dispatch or Adaptive Frequency Regulation?,” in IEEE Transactions on Power Systems, vol. 38, no. 6, pp. 5278-5289, Nov. 2023, doi: 10.1109/TPWRS.2022.3232759.
- W. Wang, X. Fang, H. Cui, F. Li, Y. Liu and T. J. Overbye, “Transmission-and-Distribution Dynamic Co-Simulation Framework for Distributed Energy Resource Frequency Response,” in IEEE Transactions on Smart Grid, vol. 13, no. 1, pp. 482-495, Jan. 2022, doi: 10.1109/TSG.2021.3118292.
- Y. Zhang et al., “Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning With Region-of-Interest Active Sampling,” in IEEE Transactions on Power Systems, vol. 37, no. 3, pp. 1942-1955, May 2022, doi: 10.1109/TPWRS.2021.3110881.
- C. Lackner, D. Osipov, H. Cui and J. H. Chow, “A Privacy-Preserving Distributed Wide-Area Automatic Generation Control Scheme,” in IEEE Access, vol. 8, pp. 212699-212708, 2020, doi: 10.1109/ACCESS.2020.3040883.
- H. Cui, F. Li, and K. Tomsovic, “Cyber-physical system testbed for power system monitoring and wide-area control verification,” IET Energy Systems Integration, vol. 2, no. 1, pp. 32-39, 2020.
Conference
- P. Basnet, X. Fang and N. Panossian, “Impact of Transportation Electrification on the System’s Dynamic Frequency Response,” 2023 IEEE Kansas Power and Energy Conference (KPEC), Manhattan, KS, USA, 2023, pp. 1-6, doi: 10.1109/KPEC58008.2023.10215428.
- F. Zelaya-Arrazabal, T. Thacker, H. Pulgar-Painemal and Z. Guo, “Supplementary Primary Frequency Control Through Deep Reinforcement Learning Algorithms,” 2023 North American Power Symposium (NAPS), Asheville, NC, USA, 2023, pp. 1-6, doi: 10.1109/NAPS58826.2023.10318681.
- K. Aleikish and T. Øyvang, “Real-Time Identification of Electromechanical Oscillations via Deep Learning Enhanced Dynamic Mode Decomposition,” 2023 IEEE Power & Energy Society General Meeting (PESGM), Orlando, FL, USA, 2023, pp. 1-5, doi: 10.1109/PESGM52003.2023.10252195.
- X. Huang, J. -Y. Gwak, L. Yu, Z. Zhang and H. Cui, “Transient Stability Preventive Control via Tuning the Parameters of Virtual Synchronous Generators,” 2023 IEEE Power & Energy Society General Meeting (PESGM), Orlando, FL, USA, 2023, pp. 1-5, doi: 10.1109/PESGM52003.2023.10253193.
- N. Parsly, J. Wang, N. West, Q. Zhang, H. Cui and F. Li, “DiME and AGVis: A Distributed Messaging Environment and Geographical Visualizer for Large-Scale Power System Simulation,” 2023 North American Power Symposium (NAPS), Asheville, NC, USA, 2023, pp. 1-5, doi: 10.1109/NAPS58826.2023.10318583.
- Y. Liu et al., “Transmission-Distribution Dynamic Co-simulation of Electric Vehicles Providing Grid Frequency Response,” 2022 IEEE Power & Energy Society General Meeting (PESGM), 2022, pp. 1-5, doi: 10.1109/PESGM48719.2022.9917027.
- H. Cui and Y. Zhang, “Andes_gym: A Versatile Environment for Deep Reinforcement Learning in Power Systems,” 2022 IEEE Power & Energy Society General Meeting (PESGM), 2022, pp. 01-05, doi: 10.1109/PESGM48719.2022.9916967.
Report
- W. Wang, X. Fang, H. Cui, J. Wang, F. Li, Y. Liu, T. J. Overbye, M. Cai, and C. Irwin, “Cyber-Physical Dynamic System (CPDS) Modeling for Frequency Regulation and AGC Services of Distributed Energy Resources,” August 2022. [Online]. Available: https://www.osti.gov/biblio/1882191.