叶宇剑

发布者：宋阳发布时间：2022-09-30浏览次数：26890

叶宇剑

职称：国家青年高层次人才、js333线路检测中心青年首席教授、博士生导师、XX青年学者、青年五四奖章获得者

研究方向:

  • 低碳城市能源-交通-信息互联网的建模、控制与分析

  • 新一代大数据与人工智能技术在电力及能源领域应用

  • 适应新型电力系统的多层次统一电力市场建模与分析

邮箱：yeyujian@seu.edu.cn

个人简介：

叶宇剑，国家高层次人才，js333线路检测中心青年首席教授、博士生导师、XX青年学者（js333线路检测中心首个），北京中关村学院兼聘博士生导师（全国首批），深圳河套学院兼聘教授（全国首批），伦敦帝国理工学院荣誉讲师、校长奖学金（全额）博士。担任英国皇家特许工程师（Charted Engineer，CEng），IEEE系统、人与控制论协会（IEEE SMC）南京分会主席，XX-js333线路检测中心宏微观一体化仿真创新实验室副主任，伦敦帝国理工学院华东校友会理事（分管智能电网方向）。IEEE、中国计算机学会、中国电机工程学会、中国电工技术学会、中国人工智能学会、中国自动化学会、亚太人工智能学会高级会员，中英人工智能学会高级研究员。


现主持国家自然科学基金项目3项（XX、面上、青年）、江苏省自然科学基金青年项目1项、CCF-腾讯犀牛鸟基金项目1项（优秀结题并获腾讯公司滚动资助）、国网/南网总部科技项目、五大发电集团科技项目、XX、腾讯等校企合作横向课题10余项，参与国家自然科学基金国际（地区）合作与交流项目1项。曾作为伦敦帝国理工学院骨干，参与欧盟委员会“地平线2020”框架项目等国际项目10余项，总投资额逾4000万英镑。


入选斯坦福全球前2%顶尖科学家榜单，作为第一/通讯作者在Nature子刊Nature Review Electrical Engineering、IEEE旗舰期刊Proceedings of the IEEE、IEEE P&E Magazine、IEEE Transactions等中科院一区Top期刊上发表高水平论文30余篇，累积影响因子破400，4篇入选ESI高被引；发表2篇CCF A类人工智能会议论文。论文入选中信所中国精品科技期刊顶尖学术论文（F5000）、中国科协科技期刊双语传播工程、IEEE PESGM最佳会议论文、中国工程院工程科技学术研讨会优秀论文，授权国家发明专利20项、国际（美国）专利2项。


担任IEEE Trans. Smart Grid、IEEE Power Engineering Letters、IEEE Trans. Industrial Informatics、Applied Energy、Protection and Control of Modern Power Systems、IEEE Trans. Industry Applications、IEEE Systems Journal等多个期刊编委；IET Smart Grid主题编辑（Subject Editor）；电力系统保护与控制、中国电力等青年编委；中国电机工程学报、IEEE Trans. Smart Grid等专题编委。担任中国人工智能学会智能自适应协同优化控制专业委员会委员、中国自动化学会能源互联网专业委员会、智能分布式能源专委会委员。


近3年获中国电力优秀青年科技人才奖、IEEE PES中国专业分会联合会优秀青年工程师奖、中国发明协会创业奖创新奖一等奖（排名第1），吴文俊人工智能优秀青年奖，中国能源研究会优秀青年能源科技工作者奖，华为挑战难题“价值火花奖”，日内瓦国际发明展银奖1项，金砖国际发明展银奖1项、江苏省自动化学会科学技术一等奖（排2）；js333线路检测中心青年五四奖章、优秀班主任标兵、优秀本科生导师、优秀本科学优生导师等荣誉。此外，带领本科生/研究生获得第十九届“挑战杯”竞赛2024年度“揭榜挂帅”专项赛特等奖、中国国际大学生创新大赛（2024）铜奖。


代表性论著：

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

  2. 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．

  3. 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．

  4. 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．

  5. 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．

  6. 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．

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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, early access.

  19. 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.

  20. 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.

  21. 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.

  22. 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.

  23. 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.

  24. 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, early access.

  25. 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, early access.

  26. 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.

  27. 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.

  28. 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.

  29. 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.

  30. 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.

  31. 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.

  32. 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.

  33. 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.

  34. 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.

  35. 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.

  36. 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.

  37. 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.

  38. 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.

  39. 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.

  40. 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.