叶宇剑
职称:上岗副研究员
研究方向: 电力市场的建模与分析、人工智能在电力及能源领域的应用、能源互联网中的建模、优化与控制、综合能源系统的运行与规划优化
Email:yeyujian@seu.edu.cn
办公电话:**

个人简介：
叶宇剑，博士，副研究员，江苏南通人，出生于1988年。2012年11月于伦敦帝国理工学院获控制系统专业硕士学位，2017年3月于伦敦帝国理工学院控制与电力研究所获电气工程专业博士学位，师从英国能源系统专家Goran Strbac教授，博士期间获伦敦帝国理工学院电气与电子工程系全额博士奖学金。同年就职于伦敦帝国理工学院任副研究员，并于帝国理工咨询公司(Imperial Consultants)兼任咨询顾问。曾参与承担多个英国、欧盟及国际重大科研/咨询项目，其中包括欧盟“地平线2020计划”下规模最大的能源项目EU-SysFlex(2000万欧元)、英国首个局域电力市场设计与试点项目Cornwall Local Energy Market(1900万英镑)、英国首个端对端能源交易及共享国际(英韩)合作项目P2P Energy Trading and Sharing - 3M(98万英镑)等。于2020年11月加入东南大学电气工程学院电力系统自动化研究所。

多年来一直从事电力市场、智能电网及能源系统领域优化和智能决策等关键问题的研究，主要研究方向包括基于人工智能的电力市场的建模与分析、能源互联网中的建模、优化与控制，电力及能源系统的运行与规划优化等国际前沿热点课题。研究成果共发表(含录用)SCI/EI论文近40篇，其中以第一作者或通讯作者IEEE Transactions on Smart Grid, IEEE Transactions on Power Systems, IEEE Internet of Things等电力、能源及物联网技术领域国际核心期刊共14篇(其中中科院一区top共7篇), 总影响因子超过85。部分研究成果收录于《电力系统经济学原理Fundamentals of Power System Economics》第二版的数个章节。2017年获得IEEE电力与能源协会最高级别学术年会IEEE PES-GM会议最佳论文奖。担任IEEE Transactions等十数个国际权威期刊审稿专家及英国工程和自然科学研究委员会(EPSRC)的基金项目评审专家。中国电机工程学会(CSEE)会员、IEEE会员、IEEE 电力及能源协会会员、IEEE控制系统协会会员、IET会员、国际能源经济协会(IAEE)会员、中国人工智能学会(CAAI)会员、中英人工智能协会(CBAIA)研究员。
论著：
期刊论文：
Y. Ye^*, D. Qiu, et. al, “Model-Free Real-Time AutonomousControl for a Residential Multi-Energy System Using Deep Reinforcement Learning,” IEEE Transactions on Smart Grid, vol. 11, no. 4, pp. 3068-3082, Jul. 2020.
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. 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, 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.
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, July. 2015.
Y. Ye, D. Qiu, et. al, Multi-period and Multi-spatial Equilibrium Analysis in Imperfect Electricity Markets: A Novel Multi-Agent Deep Reinforcement Learning Approach, IEEE Access, vol. 7, pp. 130515-130529, Sep. 2019.
Y. Ye, D. Papadaskalopoulos, et. al, Investigating the Impacts of Price-Taking and Price-Making Energy Storage in Electricity Markets through an equilibrium programming model, IET Generation, Transmission and Distribution, vol. 3, no. 2, pp. 305-315, Jan. 2019.
J. Li,Y. Ye^*, et. al, “Computationally Efficient Pricing and Benefit Distribution Mechanisms for Incentivizing Stable Peer-to-Peer Energy Trading,” IEEE Internet of Things Journal, early access.
J. Li,Y. Ye^*, et. al, “Distributed Consensus-Based Coordination of Flexible Demand and Energy Storage Resources,” IEEE Transactions on Power Systems, early access.
D. Qiu, Y.Ye^*, et. al, “A Deep Reinforcement Learning Method for Pricing Electric Vehicles with Discrete Charging Levels,” IEEE Transactions on Industry Applications, vol. 56,no. 5, pp. 5901-5912, Sept.-Oct. 2020.
J. Li, Y.Ye^*, et. al, “Stabilizing Peer-to-Peer Energy Trading in Prosumer Coalition Through Computational Efficient Pricing,” Electric Power Systems Research, vol. 189,p. 106764, Dec. 2020.
D. Qiu, Y. Ye^*, et. al, “Exploring the Effects of Local Energy Markets on Electricity Retailers and Customers,” Electric Power Systems Research, vol. 189,p. 106761, Dec. 2020.
D. Qiu, D. Papadaskalopoulos, Y. Ye^*, et. al, “Investigating the Effects of Demand Flexibility on Electricity Retailers’ Business through a Tri-Level Optimization Model,” IET Generation, Transmission and Distribution, vol. 14, no. 9, pp. 1739-1750, May 2020.
T. Oderinwale, D. Papadaskalopoulos, Y. Ye^*, et. al, “Investigating the Impact of Flexible Demand on Market-Based Generation Investment Planning,”International Journal of Electrical Power and Energy Systems, vol. 119,p. 105881, Jul. 2020.
M. Sun, Y. Wang, F. Teng, Y. Ye, et. al, “Clustering-Based Residential Baseline Estimation: A Probabilistic Perspective,” IEEE Transactions on Smart Grid, vol. 10, no. 6, pp. 6014-6028, Nov. 2019.
G. Strbac, D. Pudjianto, M. Aunedi, D. Papadaskalopoulos, P. Djapic, Y. Ye, et. al, Cost-Effective Decarbonization in a Decentralized Market: The Benefits of Using Flexible Technologies and Resources, IEEE Power and Energy Magazine, vol. 17, no. 2, pp. 25-36, Feb. 2019.
会议论文：
Y. Ye, D. Qiu, et. al, “Model-Free Real-Time Autonomous Energy Management for a Residential Multi-Carrier Energy System: A Deep Reinforcement Learning Approach,” Proc. 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), Yokohama, Japan, 11-17 July. 2020. (世界人工智能领域A+级学术会议, 2020年接收率12.6%)
D. Papadaskalopoulos, Y. Ye, et. al, Exploring the Role of Demand Shifting in Oligopolistic Electricity Markets, Proc. 2017 IEEE Power & Energy Society General Meeting(GM), Chicago, IL, USA, 16-20 July 2017. (会议最佳论文奖)
Y. Ye, D. Qiu, et. al, “A Deep Q Network Approach for Optimizing Offering Strategies in Electricity Markets,” Proc. 2^ndInternational Conference on Smart Energy Systems and Technologies (SEST), Porto, Portugal, Sep. 9-11, 2019.
Y. Ye, D. Papadaskalopoulos, et. al, Strategic capacity withholding by energy storage in electricity markets, Proc. PowerTech Conference 2017, Manchester, UK, Jun. 2017.
Y. Ye, D. Papadaskalopoulos, et. al, An MPEC approach for Analysing the Impact of Energy Storage in Imperfect Electricity Markets, Proc. 13th International Conference on the European Energy Market (EEM), Porto, Portugal, June 6-9, 2016.
Y. Ye, D. Papadaskalopoulos, et. al, Pricing Flexible Demand Non-convexities in Electricity Markets, Proc. 18th Power Systems Computation Conference (PSCC), Wroclaw, Poland, Aug. 18-22, 2014.
Y. Ye, D. Papadaskalopoulos, T. Oderinwale, and D. Qiu, A Bi-Level Optimization Modeling Framework for Investigating the Role of Flexible Demand in Deregulated Electricity Systems, submitted to 2021 IEEE Power & Energy Society General Meeting (GM), under review.
J. Li, Y.Ye,et. al, “Stabilizing Peer-to-Peer Energy Trading in Prosumer Coalition Through Computational Efficient Pricing,” Proc. 21st Power Systems Computation Conference (PSCC), Porto, Portugal, Jun. 29 - Jul. 3, 2020.
D. Qiu, Y. Ye, et. al, “Exploring the Effects of Local Energy Markets on Electricity Retailers and Customers,” Proc. 21st Power Systems Computation Conference (PSCC), Porto, Portugal, Jun. 29 - Jul. 3, 2020.
J. Li, Y. Ye, et. al, “Incentivizing Peer-to-Peer Energy Sharing Using a Core Tatonnement Algorithm,” Proc. 2020 IEEE Power & Energy Society General Meeting(GM), Montreal, Canada, 2-6 Aug. 2020.
Q. Yuan, Y. Ye, X. Liu, Q. Tian, and Y. Tang, Optimal Load Scheduling in Coupled Power and Transportation Networks, submitted to2021 IEEE Power & Energy Society General Meeting (GM), under review.
J. Li, Y. Ye, et. al, “Consensus-Based Coordination of Time-Shiftable Flexible Demand,” Proc. 2^ndInternational Conference on Smart Energy Systems and Technologies (SEST), Porto, Portugal, Sep. 9-11, 2019.
T. Oderinwale,Y. Ye, et. al, “Impact of Energy Storage on Market-Based Generation Investment Planning,” Proc. PowerTech Conference 2019, Milano, Italy, Jun. 23-27, 2019.
D. Papadaskalopoulos and Y. Ye, “Investigating the role of flexible demand and energy storage in the deregulated electricity market,” Proc. 4th Hellenic Association for Energy Economics (HAEE) Annual Symposium, “Energy Transition IV: SE Europe and beyond”, Athens, Greece, May 6-8, 2019.
D. Papadaskalopoulos, Y. Ye, et. al, “A Bi-Level Optimization Modeling Framework for Investigating the Role of Flexible Demand in Deregulated Electricity Systems,” Proc. 19th International Conference on Environment and Electrical Engineering (19th IEEE EEEIC), Genoa, Italy, Jun. 11-14, 2019.
D.Qiu, Y. Ye, et. al, “Advanced Bi-level Optimization and Reinforcement Learning Approaches for Modelling Deregulated Electricity Markets,” Proc. 2020 INFORMS Annual Meeting, Washington DC, USA, Nov. 11-14, 2020.
G.Takis-Defteraios,D. Papadaskalopoulos, Y. Ye, et. al, “Role of Flexible Demand in Supporting Market-Based Integration of Renewable Generation,” Proc. PowerTech Conference 2019, Milano, Italy, Jun. 23-27, 2019.
D. Qiu, D. Papadaskalopoulos, Y. Ye, et. al, Investigating the Impact of Demand Flexibility on Electricity Retailers, Proc. 20th Power Systems Computation Conference (PSCC), Dublin, Ireland, Jun. 11-15, 2018.
T. Oderinwale,D. Papadaskalopoulos, Y. Ye, et. al, Incorporating Demand Flexibility in Strategic Generation Investment Planning, Proc.15th International Conference on the European Energy Market (EEM), Lodz, Poland, Jun. 27-29, 2018.
项目技术报告：
D. Papadaskalopoulos, Y. Ye, et. al, “Review of electricity market design challenges and recommendations”, Report for Cornwall Local Energy Market, Mar. 2019.
K. Poncelet, A. van Stiphout, K. van den Bergh, M. Hermans, K. Bruninx, M. Ihlemann, Y. Ye, et. al, “EU-SYSFLEX Deliverable D3.4: Impact analysis of market and regulatory options through advanced power system and market modelling studies”, Report for EU-SysFlex, May 2020.
书/ 书章节:
Y. Ye, “GPS Controlled Autonomous Vehicle – An Interesting Approach to GPS Guided Autonomous Vehicle Navigation,” LAMBERT Academic Publishing, Dec. 2010.
E. Valenzuela, R. Moreno, D. Papadaskalopoulos, F. D. Mu?oz and Y. Ye, “Exploring the Concept of Hosting Capacity from an Electricity Market Perspective,” book chapter in Hosting Capacity for Modern Power Grids, Springer, in press.
科研：
2017.11 – 2021.11EU-SysFlex(欧盟“水平线2020计划”项目)
项目主要研究员，主导帝国理工科研团队在项目工作包3.2关于提高和完善电力市场设计的研究工作。开发了新的基于智能体的深度强化学习算法用于指导电力市场改革。此模型能够捕捉多个独立市场参与者的策略性竞争行为, 并评估参与者的策略性行为对市场清算结果所造成的的影响。
2016.09 – 2020.02P2P能源交易与共享(英国工程和自然科学研究委员会项目)
项目主要研究员，主导帝国理工科研团队的建模工作。此项目深入探究了能源产消者间的合作性的能源共享，设计了一个新的P2P能源交易平台的原型，促进了局域电力市场的发展。此项目也研究了能源产消者在局域电力市场的交易行为对传统供电商的商业模式的影响。
2017.09 – 2020.12Cornwall 局域电力市场(欧洲区域发展基金会项目)
项目主要研究员，主导帝国理工科研团队探索了关于局域电力市场设计所面临的核心挑战。对已有及新兴局域电力市场的设计方案进行评估，对未来局域电力市场试验项目的发展提出建设性意见。
2019.06 – 2020.06华威大学校区能源系统的实时自治能源管理(华威商学院合作项目)
项目主要研究员，主导帝国理工科研团队探索了关于局域电力市场设计所面临的核心挑战。对已有及新兴局域电力市场的设计方案进行评估，对未来局域电力市场试验项目的发展提出建设性意见。
2018.09 – 2022.02E-FLEX (Innovate UK项目)
项目主要研究员，主导帝国理工科研团队在项目工作包4.1与4.3的关于电动汽车在局域电力市场中的能源交易研究工作。我们开发了基于数据的无模型的能源管理算法来优化电动汽车的充放电方案，进而提供最优的V2G, V2H, 以及辅助服务。我们开发的局域电力市场交易机制可促使能源产消者通过优化自身电动汽车的充电方案进而与邻居分享自身过剩生产的可再生能源。
2014.09 – 2017.09储能在低碳未来的商业经济模式及规划政策(英国工程和自然科学研究委员会项目)
项目研究员参与评估了电网大规模接入储能所带来的经济价值。开发了具有多时段市场清算，考虑了输电网潮流约束的，基于博弈论的优化方法来对大型储能市场参与者的竞价行为进行建模，为储能商及储能科技投资商提供了用于优化其短期运营和长期规划决策的合适工具。

教学：
伦敦帝国理工学院：
2017-2020:硕士生、博士生联合导师
2018:大四本科生及授课型研究生课程：EE4-51 Power system economics,EE4-50 Sustainable electrical systems
2013-2017:本科生课程助教,本科生高等工程数学一对一辅导老师