叶宇剑

教授

东南大学

教育背景

教育经历（按时间倒序）：

  • 2013-2017，伦敦帝国理工学院，电气与电子工程，博士学位（全日制），校长（全额）奖学金
  • 2011-2012，伦敦帝国理工学院，控制系统，硕士学位（全日制），杰出学术贡献奖
  • 2009-2011，英国诺森比亚大学，电气与电子工程，学士学位（全日制），IET 杰出学术成就奖
  • 2007-2009，南京师范大学，电气与电子工程，学士学位（全日制）

工作经历（按时间倒序）：

  • 2025-至今，深圳河套学院，双聘教授，博导
  • 2024-至今，北京中关村学院，双聘教授，博导
  • 2023-至今，东南大学，青年首席教授，博导
  • 2022-至今，伦敦帝国理工学院，荣誉讲师
  • 2021-2022，东南大学，副教授，博导
  • 2019-2020，英国Fetch.ai，机器学习科学家
  • 2017-2019，伦敦帝国理工咨询，独立咨询顾问
  • 2016-2020，伦敦帝国理工学院，研究员
研究领域
强化学习、群体智能、智能决策、演化计算、博弈论、新型电力系统智能科学计算、AI4Energy、AI+电气化交通、电力-算力协同（Energy4AI）
邮箱
yujianye@slai.edu.cn
个人简介

叶宇剑，博士，国家高层次人才，新时代青年先锋奖，IET Fellow，东南大学青年首席教授，华为紫金青年学者，国家人工智能学院（深圳河套、北京中关村）双聘教授、博导。毕业于伦敦帝国理工学院（校长奖学金），兼任帝国理工学院荣誉讲师。主要研究方向为新型电力系统智能科学计算，主持国家自然科学基金、国家重点研发计划、国资委创新联合项目7项，在Nature子刊、Proc. IEEE, IEEE Trans等顶级期刊上发表论文40余篇，影响因子破500。担任IEEE TSG、PESL、TII、APEN等中科院一区Top期刊副主编。近三年获得中国电力优秀青年人才奖、吴文俊人工智能优秀青年奖、华为挑战难题火花奖等荣誉，带领学生获得挑战杯-揭榜挂帅专项赛特等奖、挑战杯 “人工智能+”应用赛特等奖、中国国际大学生创新大赛主赛道全国金奖、全国人工智能应用场景创新挑战赛全国总决赛特等奖等荣誉。欢迎人工智能+电力能源领域的科研合作与优秀学生报考，课题组可提供去帝国理工等世界名校的联培机会。

学术著作

代表性论文（近5-10年）：

  1. 叶宇剑，吴奕之，胡健雄，等．城市电力-交通耦合系统的联合推演与协同优化：研究综述、挑战与展望[J]．*中国电机工程学报*，2025，45(11)：4144-4163．
  2. 叶宇剑，吴奕之，胡健雄，等．市场环境下智能配用电系统分层协同优化运行：研究挑战、进展与展望[J]．中国电机工程学报，2024，44(06)：2078-2097．
  3. 叶宇剑，袁泉，刘文雯，等．基于参数共享机制多智能体深度强化学习的社区能量管理协同优化[J]．中国电机工程学报，2022，42(21)：7682-7695．
  4. 叶宇剑，袁泉, 汤奕，等. 抑制柔性负荷过响应的微网分散式调控参数优化[J]．中国电机工程学报，2022，42(05)：1748-1760．
  5. 吴奕之，*叶宇剑 (通讯作者)*，胡健雄，等．弥合配电系统恢复调度仿真现实间隙的两阶段数据机理融合优化架[J/OL] ．中国电机工程学报．
  6. 黄麒霖，*叶宇剑 (通讯作者)*，王睿，等．面向社会福利最大化的城市电动汽车充电设施自适应动态规划策略[J/OL] ．*中国电机工程学报*．
  7. 叶宇剑，王卉宇，汤奕，等．基于深度强化学习的居民实时自治最优能量管理策略[J]．电力系统自动化，2022，46(01)：110-119．
  8. 叶宇剑，王卉宇，刘曦木，等．电-碳耦合市场环境下可再生能源投资规划优化方法[J]．电力系统自动化，2023，47(23)：92-104.
  9. Y. Ye, X. Guo, et. al, “Advancing Privacy-Preserving Wind Generation Forecasts with Selective Spatial-Temporal Dependencies Extraction, Encryption and Sharing,” IEEE Transactions on Smart Grid, vol. 16, no. 4, pp. 3070-3084, July 2025.
  10. Y. Ye, Y. Tang, et. al, “Multi-agent Deep Reinforcement Learning for Coordinated Energy Trading and Ancillary Services Provision in Local Electricity Markets,” IEEE Transactions on Smart Grid, vol. 14, no. 2, pp. 1541-1554, Mar. 2023.
  11. Y. Ye, H. Wang, et. al, “Safe Deep Reinforcement Learning for Microgrid Energy Management in Distribution Networks with Leveraged Spatial-Temporal Perception,” IEEE Transactions on Smart Grid, vol. 14, no. 5, pp. 3759-3775, Sep. 2023.
  12. Y. Ye, H. Wang, et. al, “Identifying Generalizable Equilibrium Pricing Strategies for Charging Service Providers in Coupled Power and Transportation Networks,” Advances in Applied Energy, vol. 12, p. 100151, Sep. 2023.
  13. Y. Ye, Y. Tang, et. al, “A Scalable Privacy-Preserving Multi-agent Deep Reinforcement Learning Approach for Large-Scale Peer-to-Peer Transactive Energy Trading,” IEEE Transactions on Smart Grid, vol. 12, no. 6, pp. 5185-5200, Nov. 2021.
  14. Y. Ye, D. Qiu, et. al, “Deep Reinforcement Learning for Strategic Bidding in Electricity Markets,” IEEE Transactions on Smart Gird, vol. 11, no. 2, pp. 1343-1355, Mar. 2020.
  15. Y. Ye, D. Qiu, et. al, “Model-Free Real-Time Autonomous Control for a Residential Multi-Energy System Using Deep Reinforcement Learning,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 3068-3082, Jul. 2021.
  16. Y. Ye, D. Papadaskalopoulos, et. al, “Incorporating Non-Convex Operating Characteristics into Bi-Level Optimization Electricity Market Models,” IEEE Transactions on Power Systems, vol. 35, no. 1, pp. 163-176, Jan. 2020.
  17. Y. Ye, D. Papadaskalopoulos, et. al, “Investigating the ability of demand shifting to mitigate electricity producers’ market power”, IEEE Transactions on Power Systems, vol. 33, no. 4, pp. 3800-3811, Jul. 2018.
  18. Y. Ye, D. Papadaskalopoulos, et. al, “Factoring flexible demand non-convexities in electricity markets,” IEEE Transactions on Power Systems, vol. 30, no. 4, pp. 2090-2099, Jul. 2015.
  19. Y. Ye, Y. Wu, J. Hu, et. al, “Physics-Guided Safe Policy Learning with Enhanced Perception for Real-Time Dynamic Security Constrained Optimal Power Flow”, Journal of Modern Power Systems and Clean Energy, vol. 13, no. 6, pp. 1507-1519, Sep 2025.
  20. Y. Ye, D. Ma et. al, “Harvesting Spatial-Temporal Load Migration Flexibility of Data Centers: A Chance-Constrained Bi-Level Optimization Model with Endogenously Formed Risk-Reflective Locational Prices,” Applied Energy, vol. 402, Part B, p. 126971, Jan. 2026.
  21. Z. Zhu, S. Bu, KW. Chan, F. Li, Y. Ye (通讯作者), et. al, “Designing the future electricity spot market with high renewables via reliable simulations,” Nature Review Electrical Engineering, vol. 2, pp. 320-337, 2025.
  22. F. Bellizio, W. Xu, D. Qiu, Y. Ye (通讯作者), et. al, “Transition to digitalised paradigms for security control and decentralised electricity market,” Proceedings of the IEEE, vol. 111, no. 7, pp. 744-761, July 2023.
  23. X. Liu, *Y. Ye (通讯作者)*, et. al, “Towards System-Wide Satisfaction of Emission and Security Constraints for Decentralized Coordination of Carbon-Aware Virtual Power Plants in Distribution Network,” *IEEE Transactions on Smart Grid*, early access.
  24. X. Chen, *Y. Ye (通讯作者)*, et. al, “Knowledge Transferred DRL-Based Adversary for Cyberattacks on Active Distribution Network Volt-Var Control Agents: When and How,” *IEEE Transactions on Cybernetics*, early access.
  25. W.-J. Lee, Y. Ye (通讯作者), et. al, “Special Section on Integrated Operation, Planning, and Business Paradigm for Coupled Energy, Transportation, and Information Networks,” IEEE Transactions on Smart Grid, vol. 16, no. 1, pp. 455-462, Jan. 2025.
  26. Q. Ma, Y. Ye (通讯作者), et. al, “Carbon Cap Based Multi-Energy Sharing among Heterogeneous Microgrids Using Multi-Agent Safe Reinforcement Learning Method with Credit Assignment and Sequential Update,” Applied Energy, vol. 393, p. 126018, Sep. 2025.
  27. H. Liu, Y. Ye (通讯作者), et. al, “Spatiotemporal Coordination of Electric Vehicle Traffic and Energy Flows in Coupled Power-Transportation Networks with Multiple Energy Replenishment and Vehicle-to-Grid Strategies”, Applied Energy, vol. 396, p. 126291, Oct. 2025.
  28. W. Lv, Y. Ye (通讯作者), et. al, “Sustainable Electrified Seaports: A Coordinated Energy and Logistics Scheduling Approach for Future Maritime Hubs”, Applied Energy, vol. 401, Part A, p. 126645, Dec. 2025.
  29. X. Liu, Y. Ye (通讯作者), et. al, “Network-Constrained P2P Trading: A Safety-Aware Decentralized Multi-Agent Reinforcement Learning Approach,” IEEE Transactions on Smart Grid, vol. 16, no. 5, pp. 5573-5588, Nov. 2025.
  30. Q. Ma, Z. Liu, Y. Ye (通讯作者), et. al, “Carbon-Aware Peer-to-Peer Energy Trading in An Unbalanced Distribution Network via A Nash Equilibrium Discovery Deep Reinforcement Learning Approach,” IEEE Transactions on Smart Grid, vol. 16, no. 4, pp. 3070-3084, July 2025.
  31. X. Liu, Y. Ye (通讯作者), et. al, “Multi-Stage Day-Ahead and Intra-Day Resource Scheduling and Market Bidding Strategy for Integrated PV-ESS-EV Station under Multiple Uncertainties,” International Journal of Electrical Power and Energy Systems, early access.
  32. T. Cui, Y. Ye (通讯作者), et. al, “Toward Profitable Energy Futures Trading Strategies Using Reinforcement Learning Incorporating Disagreement and Connectedness Methods Enabled by Large Language Models,” Energy and AI, vol. 21, p. 100562, Sep. 2025.
  33. X. Guo, Y. Ye (通讯作者), et. al, “Leveraging Extranet Computation Security for Collaborative Wind Generation Forecasting via Secure Multiparty Computation,” CSEE Journal of Power and Energy Systems, early access.
  34. Y. Wu, Y. Ye (通讯作者), et. al, “Chance Constrained MDP Formulation and Bayesian Advantage Policy Optimization for Stochastic Dynamic Optimal Power Flow”, IEEE Transactions on Power Systems, vol. 39, no. 5, pp. 6788-6791, Sep. 2024.
  35. J. Hu, Y. Ye (通讯作者), et. al, “Rethinking Safe Policy Learning for Complex Constraints Satisfaction: A Glimpse in Real-Time Security Constrained Economic Dispatch Integrating Energy Storage Units”, IEEE Transactions on Power Systems, vol. 40, no. 1, pp. 1091-1104, Jan. 2025.
  36. J. Hu, Y. Ye (通讯作者), et. al, “Towards Risk-Aware Real-Time Security Constrained Economic Dispatch: A Tailored Deep Reinforcement Learning Approach”, IEEE Transactions on Power Systems, vol. 39, no. 2, pp. 3972-3986, Mar. 2024.
  37. H. Cui, Y. Ye (通讯作者), et. al, “Online Preventive Control for Transmission Overload Relief Using Safe Reinforcement Learning with Enhanced Spatial-Temporal Awareness,” IEEE Transactions on Power Systems, vol. 39, no. 1, pp. 517-532, Dec. 2023.
  38. H. Wang, Y. Ye (通讯作者), et. al, “An Efficient LP-based Approach for Spatial-Temporal Coordination of Electric Vehicles in Electricity-Transportation Nexus,” IEEE Transactions on Power Systems, vol. 38, no. 3, pp. 2914-2925, May 2023.
  39. J. Li, Y. Ye (通讯作者), et. al, “Distributed Consensus-Based Coordination of Flexible Demand and Energy Storage Resources,” IEEE Transactions on Power Systems, vol. 36, no. 4, pp. 3053-3069, Jul. 2021.
  40. J. Li, Y. Ye (通讯作者), et. al, “Computationally Efficient Pricing and Benefit Distribution Mechanisms for Incentivizing Stable Peer-to-Peer Energy Trading,” IEEE Internet of Things Journal, vol. 8, no. 2, pp. 734-749, Jan. 2021.
  41. Q. Yuan, Y. Ye (通讯作者), et al, “A Novel Deep-Learning based Surrogate Modeling of Stochastic Electric Vehicle Traffic User Equilibrium in Low-Carbon Electricity-Transportation Nexus,” Applied Energy, vol. 315, p. 118961, Jun. 2022.
  42. Q. Yuan, Y. Ye (通讯作者), et al, “Low Carbon Electric Vehicle Charging Coordination in Coupled Transportation and Power Networks,” IEEE Transactions on Industry Applications, vol. 59, no. 2, pp. 2162-2172, Mar./Apr. 2023.
  43. P. Chen. Y. Ye (通讯作者), et al, “Holistic Coordination of Transactive Energy and Carbon Emission Right Trading for Heterogenous Networked Multi-Energy Microgrids: A Fully Distributed Adaptive Consensus ADMM Approach,” *Sustainable Energy Technologies and Assessments*, vol. 64, p. 103729, Apr. 2024.
  44. Y. Zhang, W. Qian, Y. Ye (通讯作者), et al, “A novel non-intrusive load monitoring method based on ResNet-seq2seq networks for energy disaggregation of distributed energy resources integrated with residential houses,” Applied Energy, vol. 349, p. 121703, Aug. 2023.
  45. X. Zhang, Z. Dong, F. Huangfu, Y. Ye (通讯作者), et al, “Strategic dispatch of electric buses for resilience enhancement of urban energy systems,” Applied Energy, vol. 361, p. 122897, May 2024.
  46. Y. Wu, J. Feng, X. Chen, *Y. Ye (通讯作者)*, et al, “Enhancing Power Grid Resilience Through Weather-Aware Security Constraints: A Deep Reinforcement Learning Approach with Hybrid CNN-GRU Architecture,” *Applied Energy*, early access.

著作/编著：

  1. Y. Ye; Modelling and Analysing the Market Integration of Flexible Demand and Storage Resources; Nanjing: Southeast University Press & Springer, Aug. 2022