Research 

Selective Journal Papers [See more in Google Scholar]

[1]    Y. Zhang, X. Wang, J. Wang, and Y. Zhang, Deep reinforcement learning based volt-VAR optimization in smart distribution systems, IEEE Transactions on Smart Grid, vol.12, no.1, pp.361-371, Jan. 2021.

[2]    Y. Zhang, J. Wang, and B. Chen, Detecting false data injection attacks in smart grids: a semi-supervised deep learning approach, IEEE Transactions on Smart Grid, vol.12, no.1, pp. 623-634, Jan. 2021.

[3]    Y. Zhang, J. Wang, and M. Khodayar, Graph-based faulted line Identification using micro-PMU data in distribution systems, IEEE Transactions on Smart Grid, vol. 11, no. 5, pp. 3982-3992, Sept. 2020.

[4]    Y. Zhang and J. Wang, Towards highly efficient state estimation with nonlinear measurements in distribution systems, IEEE Transactions on Power Systems, vol. 35, no. 3, pp. 2471-2474, May 2020. 

[5]    Y. Zhang, J. Wang, and Z. Li, Interval state estimation with uncertainty of distributed generation and line parameters in unbalanced distribution systems, IEEE Transactions on Power Systems, vol. 35, no. 1, pp. 762 -772, Jan. 2020.

[6]    Y. Zhang, J. Wang, and J. Liu, Attack identification and correction for PMU GPS spoofing in unbalanced distribution systems, IEEE Transactions on Smart Grid, vol. 11, no. 1, pp. 762-773, Jan. 2020. 

[7]    Y. Zhang, J. Liang, Z. Yun, and X. Dong, A new fault-location algorithm for series-compensated double-circuit transmission lines based on the distributed parameter model, IEEE Transactions on Power Delivery. vol. 32, no. 6, pp. 2398-2407, Dec. 2017. 

[8]    Y. Zhang, J. Wang, and Z. Li, Uncertainty modeling of distributed energy resources: techniques and challenges, Current Sustainable/ Renewable Energy Report, vol. 6, no. 2, pp. 42–51, Jun. 2019.

[9]    Y. Chen, Y. Y, and Y. Zhang, A Robust SOCP-based state estimation in integrated electricity-heat system, IEEE Transactions on Smart Grid, vol.12, no.1, pp.810-820, Jan. 2021.

[10]  M. Cui, M. Khodayar, C. Chen, X. Wang, and Y. Zhang, Deep learning based time-varying parameter identification for system-wide load modeling, IEEE Transactions on Smart Grid, vol. 10, no. 6, pp. 6102-6114, Nov. 2019.

Conference Papers

[1]  S. Chung, Y. Zhang, Z. Wang, and F. Ding, Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method. 2024 IEEE PES General Meeting, Seattle, WA, pp. 1-5. (Best Paper Award)

[2] Y. Zhang, J. Zhao, D. Shi, and S. Chung, Deep Reinforcement Learning-Enabled Adaptive Forecasting-Aided State Estimation in Distribution Systems with Multi-Source Multi-Rate Data. 2024 IEEE PES Innovative Smart Grid Technologies Conference (IEEE PES ISGT NA), pp.1-5. 

[3] Y. Zhang and M. Yue, Cooperative Multi-Agent Deep Reinforcement Learning for Adaptive Decentralized Emergency Voltage Control. 2024 IEEE PES Innovative Smart Grid Technologies Conference (IEEE PES ISGT NA), pp. 1-5. (Top 5 Paper Recognition)