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 | 叶宇剑 职称:教授、博士生导师、国家青年高层次人才、东南大学青年首席教授、XX青年学者、青年五四奖章获得者 研究方向: | 
叶宇剑,国家高层次人才(青年),东南大学青年首席教授、博士生导师、XX青年学者(江南体育官网入口 首个),北京中关村学院博士生导师(东南大学首批),伦敦帝国理工学院荣誉讲师、校长奖学金(全额)博士,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-东南大学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、中国计算机学会、亚太人工智能学会高级会员。
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、国网总部科技项目、省公司科技项目等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。近年来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,XX挑战难题“价值火花奖”,东南大学青年五四奖章、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。
近5年作为第一/通讯作者在Proceedings of the IEEE、IEEE P&E Magazine、IEEE Transactions等国际权威期刊上发表中科院一区Top SCI论文25余篇,累积影响因子超过280,4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11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、IEEE Trans. Industry Applications等多个期刊编委;IET Smart Grid“Emerging Smart Grid Technologies”主题编辑;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。
代表性论著:
- Y. Ye; Modelling and Analysing the Market Integration of Flexible Demand and Storage Resources; Nanjing: Southeast University Press & Springer, Aug. 2022. 
- 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/OL].中国电机工程学报,1-20.http://kns.cnki.net/kcms/detail/ 11.2107.TM.20241223.1243.014.html. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 
- 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. 



