Publications (by area)

Sustainable Energy Systems

• Dynamic state estimation for inverter-based resources: a control-physics dual estimation framework
  H. Huang, Y. Lin, X. Lu, Y. Zhao, and A. Kumar, IEEE Transactions on Power Systems, vol. 39, no. 5, pp. 6456-6468, Sep. 2024.

• On the Equilibria and efficiency of electricity markets with renewable power producers and congestion constraints
  H. Khazaei, X. Andy Sun, and Y. Zhao, preprint. codes

• Indirect mechanism design for efficient and stable renewable energy aggregation
  H. Khazaei and Y. Zhao, IEEE Transactions on Power Systems, vol. 34, no. 2, pp. 1033-1042, Mar. 2019.

• Benefits of storage control for wind power producers in power markets
  M. Chowdhury, M. Rao, Y. Zhao, T. Javidi, and A. Goldsmith, IEEE Transactions on Sustainable Energy, vol. 7, no. 4, pp. 1492-1505, Oct. 2016.

• Wind aggregation via risky power markets
  Y. Zhao, J. Qin, R. Rajagopal, A. Goldsmith, and H. V. Poor, IEEE Transactions on Power Systems, vol. 30, no. 3, pp. 1571-1581, May 2015.

• eFlx: Provisioning of energy flexibility for E-taxi fleet
  L. Zhou, Y. Zhao, Y. Yuan, C. Xu, and S. Lin, Proc. The 16th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2025.

• Dynamic-state-estimation-based cyber attack detection for inverter-based resources
  A. Kumar, Y. Lin, H. Huang, X. Lu, and Y. Zhao, Proc. IEEE Power and Energy Society General Meeting, 2023.

• Offline reinforcement learning for price-based demand response program design
  C. Xu, B. Liu, and Y. Zhao, Proc. the 57th Annual Conference on Information Sciences and Systems (CISS), 2023.

• Net load forecast based on behind-the-meter disaggregation of smart meter data
  M. Jia, K. Pu and Y. Zhao, Proc. the 57th Annual Conference on Information Sciences and Systems (CISS), 2023.

• An Unsupervised similarity-based method for estimating behind-the-meter solar generation
  K. Pu and Y. Zhao, Proc. IEEE Conference on Innovative Smart Grid Technologies (ISGT), 2023.

• Behind-the-meter disaggregation of residential electric vehicle charging load
  K. Pu and Y. Zhao, Proc. IEEE SmartGridComm, 2022.

• Game theoretic analysis of urban e-taxi systems: equilibria and efficiency
  Y. Yuan, Y. Zhao, L. Chen, and S. Lin, Proc. IEEE International Conference on Sensing, Communication, and Networking (SECON), 2022, [Acceptance Rate: 26%.]

• POET: Towards Power-system-aware e-taxi coordination under dynamic passenger mobility
  Y. Yuan, Y. Zhao, and S. Lin, Proc. ACM e-Energy, 2022, [Acceptance Rate: 29%.]

• SOURCE: Towards Solar-uncertainty-aware e-taxi coordination under dynamic passenger mobility
  Y. Yuan, Y. Zhao, and S. Lin, Proc. American Control Conference (ACC), 2022.

• SAC: Solar-aware e-taxi fleet charging coordination under dynamic passenger mobility
  Y. Yuan, Y. Zhao, and S. Lin, Proc. IEEE Conference on Decision and Control (CDC), 2021.

• An Incentive compatible market mechanism for integrating demand response into power systems
  C. Xu, H. Khazaei, and Y. Zhao, Proc. IEEE SmartGridComm, 2020.

• Competitive market with renewable power producers achieves asymptotic social efficiency
  H. Khazaei and Y. Zhao, Proc. IEEE Power and Energy Society General Meeting, 2018.

• Solar energy sharing in net metered community microgrids: Can the social goals be achieved?
  Y. Zhao, Proc. the 52nd Annual Conference on Information Sciences and Systems (CISS), 2018.

• Ex-post stable and fair payoff allocation for renewable energy aggregation, extended version
  H. Khazaei and Y. Zhao, Proc. IEEE Conference on Innovative Smart Grid Technologies (ISGT), 2017.

• Harnessing flexible and reliable demand response under customer uncertainties
  J. Comden, Z. Liu, and Y. Zhao, Proc. ACM e-Energy, 2017, [Acceptance Rate: 25%.]

• An incentive compatible profit allocation mechanism for renewable energy aggregation
  Y. Zhao and H. Khazaei, Proc. IEEE Power and Energy Society General Meeting, 2016.

• Optimizing the level of commitment in demand response
  J. Comden, Z. Liu, and Y. Zhao, Proc. Greenmetrics, 2016.

• Value of storage for wind power producers in forward power markets
  M. Rao, M. Chowdhury, Y. Zhao, T. Javidi, and A. Goldsmith, Proc. American Control Conference (ACC), 2015.

• Risky power forward contracts for wind aggregation
  Y. Zhao, J. Qin, R. Rajagopal, A. Goldsmith, and H. V. Poor, Proc. the 51st Allerton Conference on Communication, Control and Computing (Allerton), 2013.

Learning, Inference, and Optimization in Smart Grids

• Data-driven modeling of power system dynamics: Challenges, state of the art, and future work
  H. Huang, Y. Lin, Y. Zhou, Y. Zhao, P. Zhang, L. Fan, iEnergy, vol. 2, no. 3, pp. 200-221, Sep. 2023.

• Geographically coordinated primary frequency control
  J. Comden, T. N. Le, Y. Zhao, B. J. Choi, and Z. Liu, IEEE Transactions on Control of Network Systems, vol. 6, no. 3, pp. 1246-1255, Aug. 2019.

• Control of communications-dependent cascading failures in power grids
  J. Cordova-Garcia, X. Wang, D. Xie, Y. Zhao, and L. Zuo, IEEE Transactions on Smart Grid, vol. 10, no. 5, pp. 5021-5031, Sep. 2019.

• A Learning-to-Infer method for real-time power grid multi-line outage identification
  Y. Zhao, J. Chen, and H. V. Poor, IEEE Transactions on Smart Grid, vol. 11, no. 1, pp. 555-564, Jan. 2020.

• Outage detection using load and line flow measurements in power distribution systems
  R. Sevlian, Y. Zhao, R. Rajagopal, A. Goldsmith, and H. V. Poor, IEEE Transactions on Power Systems, vol. 33, no. 2, pp. 2053-2069, Mar. 2018.

• Identification of outages in power systems with uncertain states and optimal sensor locations
  Y. Zhao, J. Chen, A. Goldsmith, and H. V. Poor, IEEE Journal of Selected Topics in Signal Processing, vol. 8, no. 6, pp. 1140-1153, Dec. 2014.

• Learning-based real-time outage location identification in power distribution systems with sparse sensors
  K. Pu, C. Xu, and Y. Zhao, Proc. IEEE SmartGridComm, 2023.

• Dynamic-state-estimation-based cyber attack detection for inverter-based resources
  A. Kumar, Y. Lin, H. Huang, X. Lu, and Y. Zhao, Proc. IEEE Power and Energy Society General Meeting, 2023.

• Offline reinforcement learning for price-based demand response program design
  C. Xu, B. Liu, and Y. Zhao, Proc. the 57th Annual Conference on Information Sciences and Systems (CISS), 2023.

• Net load forecast based on behind-the-meter disaggregation of smart meter data
  M. Jia, K. Pu and Y. Zhao, Proc. the 57th Annual Conference on Information Sciences and Systems (CISS), 2023.

• An Unsupervised similarity-based method for estimating behind-the-meter solar generation
  K. Pu and Y. Zhao, Proc. IEEE Conference on Innovative Smart Grid Technologies (ISGT), 2023.

• Integrating learning and physics based computation for fast online transient analysis
  J. Li, Y. Zhao, and M. Yue, Proc. IEEE Conference on Innovative Smart Grid Technologies (ISGT), 2023.

• Behind-the-meter disaggregation of residential electric vehicle charging load
  K. Pu and Y. Zhao, Proc. IEEE SmartGridComm, 2022.

• Fast graphical learning method for parameter estimation in large-scale distribution networks
  W. Wang, N. Yu, and Y. Zhao, Proc. IEEE SmartGridComm, 2022.

• Physics-Aware Fast Learning and Inference for Predicting Active Set of DC-OPF
  H. Khazaei and Y. Zhao, Proc. IEEE Conference on Innovative Smart Grid Technologies (ISGT), 2022.

• Machine-learning-based online transient analysis via iterative computation of generator dynamics
  J. Li, M. Yue, Y. Zhao, and G. Lin, Proc. IEEE SmartGridComm, 2020.

• Learning to Infer Voltage Stability Margin using Transfer Learning
  J. Li, Y. Zhao, Y. Lee, and S.-J. Kim, Proc. IEEE Data Science Workshop (DSW), 2019.

• Predicting voltage stability margin via learning stability region boundary
  Y. Lee, Y. Zhao, S.-J. Kim, and J. Li, Proc. IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017.

• Geographically coordinated frequency control
  J. Comden, T. N. Le, Y. Zhao, B. J. Choi, and Z. Liu, Proc. IEEE Conference on Decision and Control (CDC), 2017.

• Efficient neural network architecture for topology identification in smart grid
  Y. Zhao, J. Chen, and H. V. Poor, Proc. IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2016.

• Learning to infer: a new variational inference approach for power grid topology identification
  Y. Zhao, J. Chen, and H. V. Poor, Proc. IEEE Workshop on Statistical Signal Processing (SSP), 2016.

• Line outage detection in power transmission networks via message passing algorithms
  J. Chen, Y. Zhao, A. Goldsmith, and H. V. Poor, Proc. the 48th Asilomar Conference on Signals, Systems and Computers (Asilomar), 2014.

• Dynamic joint outage identification and state estimation in power systems
  Y. Zhao, J. Chen, A. Goldsmith, and H. V. Poor, Proc. the 48th Asilomar Conference on Signals, Systems and Computers (Asilomar), 2014.

• Optimal joint detection and estimation in linear models
  J. Chen, Y. Zhao, A. Goldsmith, and H. V. Poor, Proc. IEEE Conference on Decision and Control (CDC), 2013.

• Outage detection in power distribution networks with optimally-deployed power flow sensors
  Y. Zhao, R. Sevlian, R. Rajagopal, A. Goldsmith, and H. V. Poor, Proc. IEEE Power and Energy Society General Meeting, 2013, among PES Best Papers.

• On PMU location selection for line outage detection in wide-area transmission networks
  Y. Zhao, A. Goldsmith, and H. V. Poor, Proc. IEEE Power and Energy Society General Meeting, 2012.

Security in Power Networks

• Dynamic-state-estimation-based cyber attack detection for inverter-based resources
  A. Kumar, Y. Lin, H. Huang, X. Lu, and Y. Zhao, Proc. IEEE Power and Energy Society General Meeting, 2023.

• Minimum sparsity of unobservable power network attacks
  Y. Zhao, A. Goldsmith, and H. V. Poor, IEEE Transactions on Automatic Control, vol. 62, no. 7, pp. 3354-3368, Jul. 2017. codes

• Generic cospark of a matrix can be computed in polynomial time
  S. Zhong and Y. Zhao, Proc. IEEE International Symposium on Information Theory (ISIT), 2017.

• A polynomial-time method to find the sparsest unobservable attacks in power networks
  Y. Zhao, A. Goldsmith, and H. V. Poor, Proc. American Control Conference (ACC), 2016.

• Fundamental limits of cyber-physical security in smart power grids
  Y. Zhao, A. Goldsmith, and H. V. Poor, Proc. IEEE Conference on Decision and Control (CDC), 2013.

Communication Networks

• Optimal spectrum management in multiuser interference channels
  Y. Zhao and G. J. Pottie, IEEE Transactions on Information Theory, vol. 59, no. 8, pp. 4961-4976, Aug. 2013.

• On the maximum achievable sum-rate with successive decoding in interference channels
  Y. Zhao, C. W. Tan, A. S. Avestimehr, S. N. Diggavi, and G. J. Pottie, IEEE Transactions on Information Theory, vol. 58, no. 6, pp. 3798-3820, Jun. 2012.

• Convex optimization for precoder design in MIMO interference networks
  Y. Zhao, S. N. Diggavi, A. Goldsmith, and H. V. Poor, Proc. the 50th Allerton Conference on Communication, Control and Computing (Allerton), 2012.

• On the sum-capacity with successive decoding in interference channels
  Y. Zhao, C. W. Tan, A. S. Avestimehr, S. N. Diggavi, and G. J. Pottie, Proc. IEEE International Symposium on Information Theory (ISIT), 2011.

• Interference strength alignment and uplink channel allocation in linear cellular networks
  Y. Zhao and G. J. Pottie, Proc. IEEE International Conference on Communications (ICC), 2011.

• Optimization of power and channel allocation using the deterministic channel model
  Y. Zhao and G. J. Pottie. Proc. Information Theory and Applications Workshop (ITA), 2010.

• Optimal spectrum management in multiuser interference channels
  Y. Zhao and G. J. Pottie, Proc. IEEE International Symposium on Information Theory (ISIT), 2009.

• Optimal spectrum management in two-user symmetric interference channels
  Y. Zhao and G. J. Pottie, Proc. Information Theory and Applications Workshop (ITA), 2009.

Miscellaneous

• DeepPursuit: Uniting classical wisdom and deep RL for sparse recovery
  Z. Chen, S. Zhong, J. Chen, and Y. Zhao, Proc. the 55th Asilomar Conference on Signals, Systems and Computers (Asilomar), 2021.

• Learning to recover sparse signals
  S. Zhong, Y. Zhao, and J. Chen, Proc. the 57th Allerton Conference on Communication, Control and Computing (Allerton), 2019.

• New formulation and optimization methods for water sensor placement
  Y. Zhao, R. Schwartz, E. Salomons, A. Ostfeld, and H. V. Poor, Journal of Environmental Modelling & Software, vol. 76, pp. 128-136, Feb. 2016.