| Intelligent Multi-microgrid Energy Management based on Deep Neural Network and Model-free Reinforcement Learning Y Du, F Li IEEE Transactions on Smart Grid, 2019 | 204 | 2019 |
| A cooperative game approach for coordinating multi-microgrid operation within distribution systems Y Du, W Zhiwei, L Guangyi, X Chen, H Yuan, W Yanli, F Li Applied Energy 222, 383-395, 2018 | 143 | 2018 |
| Optimal bidding strategy and intramarket mechanism of microgrid aggregator in real-time balancing market W Pei, Y Du, W Deng, K Sheng, H Xiao, H Qu IEEE Transactions on Industrial Informatics 12 (2), 587-596, 2016 | 132 | 2016 |
| Intelligent multi-zone residential HVAC control strategy based on deep reinforcement learning Y Du, H Zandi, O Kotevska, K Kurte, J Munk, K Amasyali, E Mckee, F Li Applied Energy 281, 2020 | 112 | 2020 |
| Temporal-spatial analysis and improvement measures of Chinese power system for wind power curtailment problem W Pei, Y Chen, K Sheng, W Deng, Y Du, Z Qi, L Kong Renewable and Sustainable Energy Reviews 49, 148-168, 2015 | 81 | 2015 |
| From AlphaGo to Power System AI: What Engineers Can Learn from Solving the Most Complex Board Game F Li, Y Du IEEE Power and Energy Magazine 16 (2), 76-84, 2018 | 77 | 2018 |
| Achieving 100x Acceleration for N-1 Contingency Screening with Uncertain Scenarios using Deep Convolutional Neural Network Y Du, F Li, J Li, T Zheng IEEE Transactions on Power Systems, 2019 | 62 | 2019 |
| A Hierarchical Real-time Balancing Market Considering Multi-microgrids with Distributed Sustainable Resources Y Du, F Li IEEE Transactions on Sustainable Energy, 2018 | 59 | 2018 |
| Real-time microgrid economic dispatch based on model predictive control strategy D Yan, P Wei, N Chen, X Ge, X Hao Journal of Modern Power Systems and Clean Energy, 2017 | 46 | 2017 |
| Emerging smart grid technology for mitigating global warming X Zhang, W Pei, W Deng, Y Du, Z Qi, Z Dong International Journal of Energy Research 39 (13), 1742-1756, 2015 | 41 | 2015 |
| Multi-task deep reinforcement learning for intelligent multi-zone residential HVAC control Y Du, F Li, J Munk, K Kurte, O Kotevska, K Amasyali, H Zandi Electric Power Systems Research 192, 106959, 2021 | 35 | 2021 |
| Approximating Nash Equilibrium in Day-ahead Electricity Market Bidding with Multi-agent Deep Reinforcement Learning Y Du, F Li, H Zandi, Y Xue Journal of Modern Power Systems and Clean Energy, 2021 | 33 | 2021 |
| Novel solution and key technology of interconnection and interaction for large scale microgrid cluster integration PEI Wei, DU Yan, LI Hongtao, Y Yanhong, D Wei High Voltage Engineering 41 (10), 3193-3203, 2015 | 31 | 2015 |
| Model-Based and Data-Driven HVAC Control Strategies for Residential Demand Response X Kou, Y Du, F Li, H Pulgar-Painemal, H Zandi, J Dong, MM Olama IEEE Open Access Journal of Power and Energy, 2021 | 23 | 2021 |
| Evaluating the adaptability of reinforcement learning based HVAC control for residential houses K Kurte, J Munk, O Kotevska, K Amasyali, R Smith, E McKee, Y Du, B Cui, ... Sustainability 12 (18), 7727, 2020 | 19 | 2020 |
| Fast Cascading Outage Screening based on Deep Convolutional Neural Network and Depth-First Search Y Du, F Li, T Zheng, J Li IEEE Transactions on Power Systems, 2020 | 18 | 2020 |
| Coordinating Multi-microgrid Operation within Distribution System: A Cooperative Game Approach Y Du, F Li, X Kou, W Pei Power & Energy Society General Meeting, 2017 IEEE, 1-5, 2018 | 18 | 2018 |
| Deep Reinforcement Learning from Demonstrations to Assist Service Restoration in Islanded Microgrids Y Du, D Wu IEEE Transactions on Sustainable Energy, 2022 | 16 | 2022 |
| Optimal operation of microgrid with photovoltaics and gas turbines in demand response W Pei, Y Du, H Xiao, Z Shen, W Deng, Y Yang 2014 International Conference on Power System Technology, 3058-3063, 2014 | 12 | 2014 |
| Learning and fast adaptation for grid emergency control via deep meta reinforcement learning R Huang, Y Chen, T Yin, Q Huang, J Tan, W Yu, X Li, A Li, Y Du IEEE Transactions on Power Systems, 2022 | 11 | 2022 |
Fangxing (Fran) LiJames W. McConnell Professor at University of Tennessee, IEEE Fellow, EIC of IEEE OAJPEVerified email at utk.edu
