Showcase of LTB

Table of Contents

Getting Started

Quick Start Guide

Research Demo

  1. Disturbance Propagation in Power Grids With High Converter Penetration by Dr. Hantao Cui
  2. Transmission-and-Distribution Co-Simulation Framework by Dr. Xin Fang
  3. Electric Vehicles Charging Time Constrained Deliverable Provision of Secondary Frequency Regulation by Jinning Wang
  4. Virtual Inertia Scheduling (VIS) for Real-time Economic Dispatch by Buxin She
  5. Virtual Inertia Scheduling (VIS) for Microgrids with Static and Dynamic Security Constraints by Buxin She

Presentations and Talks

  1. DiME and AGVis: Distributed Messaging Environment and Geographical Visualizer for CURENT Large-scale Testbed (LTB) by Jinning Wang
  2. Advancing a Decarbonized Power Grid: A Transient Stability Perspective with LTB - Talk at UTK ECE522 Course by Jinning Wang
  3. CURENT Large-scale Testbed (LTB) - A Comprehensive Power System Testing Platform, Presentation at CURENT Industry Conference 2023 by Jinning Wang
  4. CURENT Large-scale Testbed (LTB), A seminar at Stanford in April 2021 by Dr. Fangxing (Fran) Li

Publications with LTB Support

Journal

  1. H. Cui et al., “Disturbance Propagation in Power Grids With High Converter Penetration,” in Proceedings of the IEEE, doi: 10.1109/JPROC.2022.3173813.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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

  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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

  1. 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.