| Safe off-policy deep reinforcement learning algorithm for volt-var control in power distribution systems W Wang, N Yu, Y Gao, J Shi IEEE Transactions on Smart Grid 11 (4), 3008-3018, 2019 | 264 | 2019 |
| Consensus multi-agent reinforcement learning for volt-var control in power distribution networks Y Gao, W Wang, N Yu IEEE Transactions on Smart Grid 12 (4), 3594-3604, 2021 | 131 | 2021 |
| Operating electric vehicle fleet for ride-hailing services with reinforcement learning J Shi, Y Gao, W Wang, N Yu, PA Ioannou IEEE Transactions on Intelligent Transportation Systems 21 (11), 4822-4834, 2019 | 127 | 2019 |
| Batch-constrained reinforcement learning for dynamic distribution network reconfiguration Y Gao, W Wang, J Shi, N Yu IEEE Transactions on Smart Grid 11 (6), 5357-5369, 2020 | 125 | 2020 |
| A physically inspired data-driven model for electricity theft detection with smart meter data Y Gao, B Foggo, N Yu IEEE Transactions on Industrial Informatics 15 (9), 5076-5088, 2019 | 101 | 2019 |
| Learning to operate an electric vehicle charging station considering vehicle-grid integration Z Ye, Y Gao, N Yu IEEE transactions on smart grid 13 (4), 3038-3048, 2022 | 74 | 2022 |
| Multi-agent deep reinforcement learning for voltage control with coordinated active and reactive power optimization D Hu, Z Ye, Y Gao, Z Ye, Y Peng, N Yu IEEE Transactions on Smart Grid 13 (6), 4873-4886, 2022 | 66 | 2022 |
| Model-augmented safe reinforcement learning for Volt-VAR control in power distribution networks Y Gao, N Yu Applied Energy 313, 118762, 2022 | 44 | 2022 |
| Volt-VAR control in power distribution systems with deep reinforcement learning W Wang, N Yu, J Shi, Y Gao 2019 IEEE International Conference on Communications, Control, and Computing …, 2019 | 44 | 2019 |
| Optimal placement and intelligent smoke detection algorithm for wildfire-monitoring cameras J Shi, W Wang, Y Gao, N Yu IEEE Access 8, 72326-72339, 2020 | 40 | 2020 |
| Dynamic distribution network reconfiguration using reinforcement learning Y Gao, J Shi, W Wang, N Yu 2019 IEEE International Conference on Communications, Control, and Computing …, 2019 | 39 | 2019 |
| State estimation for unbalanced electric power distribution systems using AMI data Y Gao, N Yu 2017 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2017 | 32 | 2017 |
| Deep reinforcement learning in power distribution systems: Overview, challenges, and opportunities Y Gao, N Yu 2021 IEEE power & energy society innovative smart grid technologies …, 2021 | 21 | 2021 |
| Solving unit commitment problems with multi-step deep reinforcement learning J Qin, N Yu, Y Gao 2021 IEEE international conference on communications, control, and computing …, 2021 | 18 | 2021 |
| Deep reinforcement learning-based two-timescale Volt-VAR control with degradation-aware smart inverters in power distribution systems F Kabir, N Yu, Y Gao, W Wang Applied Energy 335, 120629, 2023 | 15 | 2023 |
| A robust segmented mixed effect regression model for baseline electricity consumption forecasting X Zhou, Y Gao, W Yao, N Yu Journal of Modern Power Systems and Clean Energy 10 (1), 71-80, 2020 | 15 | 2020 |
| Harnessing deep reinforcement learning to construct time-dependent optimal fields for quantum control dynamics Y Gao, X Wang, N Yu, BM Wong Physical Chemistry Chemical Physics 24 (39), 24012-24020, 2022 | 12 | 2022 |
| Routing electric vehicle fleet for ride-sharing J Shi, Y Gao, N Yu 2018 2nd IEEE Conference on Energy Internet and Energy System Integration …, 2018 | 10 | 2018 |
| Degradation-aware valuation and sizing of behind-the-meter battery energy storage systems for commercial customers Z Zhang, J Shi, Y Gao, N Yu 2019 IEEE PES GTD Grand International Conference and Exposition Asia (GTD …, 2019 | 9 | 2019 |
| Reinforcement learning-based smart inverter control with polar action space in power distribution systems F Kabir, Y Gao, N Yu 2021 IEEE Conference on Control Technology and Applications (CCTA), 315-322, 2021 | 8 | 2021 |
Nanpeng YuUniversity of California, Riverside在 ece.ucr.edu 的电子邮件经过验证
