• G. Tian, Q. Z. Sun, and W. Wang, “Real-time Flexibility Quantification of a Building HVAC System for Peak Demand Reduction,” IEEE Transactions on Power Systems, early access, 2022.
  • S. Faddel, Q. Zhou, and G. Tian, “Modeling and Coordination of Commercial Buildings in Distribution Systems,” IEEE Transactions on Industry Applications, early access, 2022.
  • W. Wang, Q. Zhou, C. Pan, and F. Cao, “Energy-Efficient Operation of a Complete Chiller-Air Handing Unit System via Model Predictive Control,” Applied Thermal Engineering, vol. 201, Jan. 2022.
  • H. Panamtash, Q. Z. Sun, Y. Rubin, P. Brooker, and J. Kramer, “Solar Power Smoothing in a Nanogrid Testbed,” 2022 IEEE PES Transmission & Distribution Conference & Exposition (T&D), New Orleans, LA. USA, Apr. 2022.
  • S. Faddel and Q. Z. Sun, “Scheduling of the HVAC System in a Real Commercial Building Considering Equipment Cycling and Rebound Effects,” 2022 IEEE PES Innovative Smart Grid Technologies (ISGT), Washington DC, Feb 2022.
  • G. Tian and Q. Z. Sun, “Chance Constrained Distributionally Robust Optimal HVAC Scheduling for Commercial Building Demand Response,” 2022 IEEE PES Innovative Smart Grid Technologies (ISGT), Washington DC, Feb. 2022.


  • W. Wang, Z. Zhao, Q. Zhou, Y. Qiao, and F. Cao, “Model Predictive Control for the Operation of a Transcritical CO2 Air Source Heat Pump Water Heater,” Applied Energy, to appear. 
  • Mahdavi, H. Panamtash*, A. Dimitrovski, Q. Zhou, “Predictive Coordinated and Cooperative Voltage Control for Systems with High Penetration of PV,” IEEE Transactions on Industry Applications, vol 57., no. 3, pp. 2212-2222, May 2021.
  • W. Wang, Q. Zhou, G. Tian, Y. Wang, Z. Zhao, F. Cao, “A Novel Defrosting Initiation Strategy based on Convolutional Neural Network for Air-Source Heat Pump,” International Journal of Refrigeration, April 2021. 
  • S. Faddel, G. Tian, and Q. Zhou, “Decentralized Management of Commercial HVAC Systems,” Energies, vol 14, May 2021. 
  • G. Tian, Y. Gu, Y. Zhe, D. Shi, Q. Zhou, “Enhanced Denosing Autoencoder Aided Bad Data Filtering for Synchrophasor-based State Estimation,” CSEE Journal of Power and Energy Systems, to appear.
  • M. Safayatullah, Q. Zhou, and I. Batarseh, “Smoothing of PV Output Power in Grid-Tied Energy Storage System with Model Predictive Control and Battery Lifetime Consideration,” IEEE Energy Conversion Congress & Expo, Vancouver, Canada, Oct. 2021.
  • M. Cash, S. Wang, B. Pearson, Q. Zhou, and X. Fu, “On Automating BACnet Device Discovery and Property Identification,” IEEE 2021 IEEE International Conference on Communications (ICC): Communication and Information Systems Security Symposium, Virtual/Montreal, Canada, 14-23 June 2021.


  • H. Panamtash, Q. Zhou, T. Hong, Z. Qu, and K. O. Davis,  “A Copula-based Bayesian Method for Probabilistic Solar Power Forecasting,” Solar Energy, vol. 196, pp. 336-345, Jan. 2020.
  • E. Elliot, N. Shanklin, S. Zehtabian, Q. Zhou, and D. Turgut, “Peer-to-Peer Energy Trading and Grid Impact Studies  in Smart Communities”, 2020 International Conference on Computing, Networking and Communications (ICNC), Big Island, HI, Feb. 2020.
  • G. Tian, S. Faddel, Q. Zhou, Z. Qu, and A. Parlato, “Optimal Coordination of HVAC Scheduling for Commercial Buildings”, 2020 Texas Power and Energy Conference (TPEC), College Station, TX, Feb. 2020.
  • G. Tian, R. Birari, Q. Zhou, Z. Qu, and J. Qi, “A Hybrid-Learning Algorithm for Online Dynamic State Estimation in Multi-Machine Power Systems”, IEEE Transactions on Neural Networks and Learning Systems, to appear.
  • L. Wang, Q. Zhou, and S. Jin,  “Physics-Guided Deep Learning for Power System State Estimation”, Journal of Modern Power System and Clean Energy, to appear.


  • S. Wang, L. Du, and Q. Zhou, “A Semi-Supervised Deep Transfer Learning Architecture for Energy Disaggregation“, 2019 IEEE PES General Meeting, Atlanta, GA, Aug. 2019
  • L. Wang, and Q. Zhou, “Physics-Guided Deep Learning for Time-Series State Estimation Against False Data Injection Attacks”, 51st North American Power Symposium, Wichita, KS, Oct. 2019.


  • H. Panamtash and Q. Zhou, “Coherent probabilistic solar power forecasting,” 15th International Conference on Probabilistic Methods Applied to Power Systems, Boise, ID, June 24 – 28, 2018.
  • G. Tian, Q. Zhou, and L. Du, “Deep convolutional neural networks for distribution system fault classification,” 2018 IEEE PES General Meeting, Portland, OR, August 5-10, 2018.
  • A. Golshani, W. Sun, Q. Zhou, Q.P. Zheng, J. Wang, and F. Qiu, “Coordination of wind farm and pumped-storage hydro for a self-healing power grid,” IEEE Transactions on Sustainable Energy, vol.9, no. 4, pp. 1910-1920, Oct 2018.


  • A. Golshani, W. Sun, Q. Zhou, Q.P. Zheng, and J. Tong, “Two-stage adaptive restoration decision support system for a self-healing power grid,” IEEE Transactions on Industrial Informatics, vol. 13, no. 6, pp. 2802-2812, 2017.
  • A. Golshani, W. Sun, Q. Zhou, Q. P. Zheng, and Y. Hou, “Incorporating wind energy in power system restoration planning,” IEEE Transactions on Smart Grid, 2017.

Prior Years

  • A. Golshani, W. Sun, and Q. Zhou, “PHEVs’ contribution to self-healing process of distribution systems,” 2016 IEEE Power & Energy Society General Meeting, Boston, MA, Jul. 2016.
  • D. Chaudhary, W. Sun, Q. Zhou, and A. Golshani, “Chance-constrained real-time volt/var optimization using simulated annealing,” 2015 IEEE Power & Energy Society General Meeting, Denver, CO, Jul. 2015.
  • A. Golshani, W. Sun, and Q. Zhou, “Optimal PMU placement for power system restoration,” 2015 Power Systems Conference, Clemson University, 2015.
  • N. Kadel, W. Sun, and Q. Zhou, “On battery storage system for load pickup in power system restoration,” 2014 IEEE Power & Energy Society General Meeting, National Harbor, MD, 27-31 Jul. 2014.
  • Q. Zhou, L. Tesfatsion, C. C. Liu, R. F. Chu, and W. Sun, “A Nash approach to planning merchant transmission for renewable resource integration,” IEEE Transactions on Power Systems, vol. 28, no. 3,pp. 2086-2100, Aug. 2013.
  • W. Sun and Q. Zhou, “Maintenance strategies for a generation company in a CO2 allowance market environment,”2012 IEEE Power & Energy Society General Meeting, San Diego, CA, Jul. 2012.
  • Q. Zhou, W. Guan and W. Sun, “Impact of demand response contracts on load forecasting in a smart grid environment,” Invited paper, 2012 IEEE Power & Energy Society General Meeting, San Diego, CA, Jul. 2012.
  • W. Sun, P. Zhang and Q. Zhou, “Optimization-based strategies towards a self-healing smart grid,” 2012 IEEE Power & Energy Society Innovative Smart Grid Technologies Asia , Tianjin, China, May 2012.
  • Q. Zhou, L. Tesfatsion, C. C. Liu, “Short-term congestion forecasting in wholesale power market, “IEEE Transactions on Power Systems, vol. 26, no. 4,pp. 2185-2196, Nov. 2011.
  • Q. Zhou, L.Tesfatsion, and C. C. Liu, “Global sensitivity analysis for the short-term prediction of system variables,” 2010 IEEE Power & Energy Society General Meeting, Minneapolis, MN, Jul. 2010.
  • Q. Zhou, L. Tesfatsion, and C. C. Liu, “Scenario generation for price forecasting in restructured wholesale power markets,” IEEE Power Systems Conference & Exposition, Seattle, WA, Mar. 2009.