| Deep-reinforcement-learning-based autonomous voltage control for power grid operations J Duan, D Shi, R Diao, H Li, Z Wang, B Zhang, D Bian, Z Yi IEEE Transactions on Power Systems 35 (1), 814-817, 2019 | 363 | 2019 |
| A data-driven multi-agent autonomous voltage control framework using deep reinforcement learning S Wang, J Duan, D Shi, C Xu, H Li, R Diao, Z Wang IEEE Transactions on Power Systems 35 (6), 4644-4654, 2020 | 263 | 2020 |
| Modeling, control, and protection of modular multilevel converter-based multi-terminal HVDC systems: A review L Zhang, Y Zou, J Yu, J Qin, V Vittal, GG Karady, D Shi, Z Wang CSEE Journal of Power and Energy Systems 3 (4), 340-352, 2017 | 252 | 2017 |
| A Monte Carlo simulation approach to evaluate service capacities of EV charging and battery swapping stations T Zhang, X Chen, Z Yu, X Zhu, D Shi IEEE Transactions on Industrial Informatics 14 (9), 3914-3923, 2018 | 162 | 2018 |
| Reinforcement-learning-based optimal control of hybrid energy storage systems in hybrid AC–DC microgrids J Duan, Z Yi, D Shi, C Lin, X Lu, Z Wang IEEE Transactions on Industrial Informatics 15 (9), 5355-5364, 2019 | 155 | 2019 |
| Identification of short transmission-line parameters from synchrophasor measurements D Shi, DJ Tylavsky, N Logic, KM Koellner 2008 40th North American Power Symposium, 1-8, 2008 | 152 | 2008 |
| Transmission line parameter identification using PMU measurements D Shi, DJ Tylavsky, KM Koellner, N Logic, DE Wheeler European Transactions on Electrical Power 21 (4), 1574-1588, 2011 | 141 | 2011 |
| Autonomous voltage control for grid operation using deep reinforcement learning R Diao, Z Wang, D Shi, Q Chang, J Duan, X Zhang 2019 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2019 | 133 | 2019 |
| An Adaptive Method for Detection and Correction of Errors in PMU Measurements D Shi, DJ Tylavsky, N Logic IEEE Transactions on Smart Grid 3 (4), 1575-1583, 2012 | 133 | 2012 |
| A blockchain-enabled multi-settlement quasi-ideal peer-to-peer trading framework MK AlAshery, Z Yi, D Shi, X Lu, C Xu, Z Wang, W Qiao IEEE Transactions on Smart Grid 12 (1), 885-896, 2020 | 123 | 2020 |
| Optimization of battery energy storage to improve power system oscillation damping Y Zhu, C Liu, K Sun, D Shi, Z Wang IEEE Transactions on Sustainable Energy 10 (3), 1015-1024, 2018 | 116 | 2018 |
| Thermostatic load control for system frequency regulation considering daily demand profile and progressive recovery Q Shi, F Li, G Liu, D Shi, Z Yi, Z Wang IEEE Transactions on Smart Grid 10 (6), 6259-6270, 2019 | 92 | 2019 |
| Online identification and data recovery for PMU data manipulation attack X Wang, D Shi, J Wang, Z Yu, Z Wang IEEE Transactions on Smart Grid 10 (6), 5889-5898, 2019 | 91 | 2019 |
| A data-driven method for fast ac optimal power flow solutions via deep reinforcement learning Y Zhou, B Zhang, C Xu, T Lan, R Diao, D Shi, Z Wang, WJ Lee Journal of Modern Power Systems and Clean Energy 8 (6), 1128-1139, 2020 | 89 | 2020 |
| A deep reinforcement learning-based multi-agent framework to enhance power system resilience using shunt resources M Kamruzzaman, J Duan, D Shi, M Benidris IEEE Transactions on Power Systems 36 (6), 5525-5536, 2021 | 83 | 2021 |
| Electric vehicles participation in load frequency control based on mixed H2/H∞ M Khan, H Sun, Y Xiang, D Shi International Journal of Electrical Power & Energy Systems 125, 106420, 2021 | 81 | 2021 |
| Small-signal stability analysis and performance evaluation of microgrids under distributed control Y Yan, D Shi, D Bian, B Huang, Z Yi, Z Wang IEEE Transactions on Smart Grid 10 (5), 4848-4858, 2018 | 80 | 2018 |
| Consensus-based distributed cooperative control for microgrid voltage regulation and reactive power sharing D He, D Shi, R Sharma IEEE PES Innovative Smart Grid Technologies, Europe, 1-6, 2014 | 79 | 2014 |
| A distributed cooperative control framework for synchronized reconnection of a multi-bus microgrid D Shi, X Chen, Z Wang, X Zhang, Z Yu, X Wang, D Bian IEEE Transactions on Smart Grid 9 (6), 6646-6655, 2017 | 76 | 2017 |
| Two-stage WECC composite load modeling: A double deep Q-learning networks approach X Wang, Y Wang, D Shi, J Wang, Z Wang IEEE Transactions on Smart Grid 11 (5), 4331-4344, 2020 | 72 | 2020 |
