叶宇剑

发布者:宋阳发布时间:2020-12-24浏览次数:3199

叶宇剑

职称:  上岗副研究员、硕士生导师

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、能源互联网的建模、优化与控制

Email: yeyujian@seu.edu.cn

办公电话: 13851918258

每年招收对人工智能在电力系统应用感兴趣、且有一定数学建模功底编程基础的研究生,

欢迎有志之士加入研究团队!


个人简介:

叶宇剑,博士,副研究员,硕士生导师,IEEE Senior Member,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。主持江苏省“双创博士”世界名校类项目申请人作为伦敦帝国理工科研团队核心技术与领导人员参与了多个英国、欧洲及国际科研项目,包括欧盟“地平线2020计划”下规模最大的能源项目EU-SysFlex2000万欧元)和TradeRES400万英镑)、英国首个本地电力市场设计与试点项目Cornwall Local Energy Market1900万英镑)、英国首个端对端能源交易及共享英韩联合项目P2P Energy Trading and Sharing - 3M98万英镑)等。20211月加入东南大学电气工程学院。

2021.1至今

东南大学

副研究员

2021.3至今

伦敦帝国理工学院

访问学者

2019-2020

英国Fetch.ai人工智能公司

机器学习科学家

2016-2019

伦敦帝国理工学院

博士后

2016-2019

帝国理工咨询Imperial Consultant

咨询顾问

2013-2017

伦敦帝国理工学院

博士

2011-2012

伦敦帝国理工学院

硕士

2013 年以来,以第一作者或通讯作者在《中国电机工程学报》、《电力系统自动化》、《IEEE Transactions on Power Systems》、《IEEE Transactions on Smart Grid》、《Applied Energy等国内外高水平学术期刊上发表论文共22篇(其中JCR一区SCI论文12篇,中科院一区top 9篇),累积影响因子超过120;发表21 EI 国际会议论文(其中一篇为世界人工智能A级会议IJCAI2020,一篇论文获IEEE PESGM 2017会议最佳论文奖)。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。

受邀担任IET Energy Systems Integration》、《IET Smart Grid》期刊编委,《中国电机工程学报》、《中国电力》、《Frontiers in Energy Research》期刊专题编委;长期担任英国工程和自然科学研究委员会基金项目的评审专家;长期担任国内外顶级学术期刊审稿人,2020年获得《IEEE Transactions on Power Systems》杰出审稿人2021年获得《电力系统自动化》优秀审稿人2017年获International Journal of Electrical Power and Energy Systems 杰出审稿人;担任英国工程自然科学研究委员会(EPSRC)基金项目评审专家。


担任IEEE高级会员、中国电机工程学会(CSEE)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;IEEE PES智能电网与新技术委员会(中国) - 智能电网与人工智能分委会理事,IEEE PES电力系统运行、规划与经济技术委员会(中国) - 电力市场技术分委会理事,IEEE PES 电力系统动态技术委员会(中国) - 动态电力系统人工智能应用技术分委会理事


  主持/参与的项目:

  1. 2021年江苏省“双创博士”项目,JSSCBS20211013715万元,在研,主持;

  2. 国家电网江苏省电力有限公司业务研究项目,基于区域试点先行的分布式绿电现货运营机制研究,2022-012022-1235万元,在研,主持;

  3. 南方电网深圳供电局有限公司项目,智能电网调度全景AI指挥平台关联技术研究与应用,2020-102022.10,在研,参与

  4. 英国工程和自然科学研究委员会,英韩联合项目, EP/N03466X/1Peer-to-peer energy trading and sharing - 3M (Multi-times, Multi-scales, Multi-qualities), 2016-092020-02, 98万英镑,结题,参与;

  5. 欧洲地区发展基金会,英国首个本地能量市场项目,Cornwall local energy market2017.092020.121900万英镑,结题,参与;

  6. Innovate UK104249E-FLEX - Real-world Energy Flexibility through Electric Vehicle Energy Trading2018.092022.0237万英镑,结题,参与;

  7. 英国工程和自然科学研究委员会,中英联合项目,EP/T021780/1Technology Transformation to Support Flexible and Resilient Local Energy Systems2020-072023-0381万英镑,在研,参

  8. 欧盟“水平线2020计划”,欧盟委员会项目,773505EU-Sysflex (Pan-European system with an efficient coordinated use of flexibilities for the integration of a large share of RES)2017.112021.112000万欧元,结题,参与;

  9. 欧盟“水平线2020计划”,欧盟委员会项目,864276TradeRES – Tools for the Design and Modelling of New Markets and Negotiation Mechanisms for a 100% Renewable European Power System400万英镑,2020.022023.02,在研,参与;

  10. 英国工程和自然科学研究委员会,面上项目,EP/R045518/1Integrated Development of Low-Carbon Energy Systems (IDLES): A Whole-System Paradigm for Creating a National Strategy2018-112023-10705万英镑,在研,参加。

  1. 英国工程和自然科学研究委员会,中英联合项目,EP/L014386/1Business, economics, planning and policy for energy storage in low-carbon futures, 2014-092017-09100万英镑,结题,参与;

  2. 英国工程和自然科学研究委员会,中英联合项目,EP/L001039/1Grid Economics, Planning and Business Models for Smart Electric Mobility2013-122016-12100万英镑,结题,参与;

  3. 英国工程和自然科学研究委员会,面上项目,EP/T022949/1Zero-Carbon Emission Integrated Cooling, Heating and Power (ICHP) Network2021-012023-12115万英镑,在研,参加。

  4. 英国工程和自然科学研究委员会,面上项目,EP/V012053/1The Active Building Centre Research Programme (ABC RP)2020-042022-09932万英镑,在研,参加。

  5. Economic and Social Research Council,面上项目,ES/T000112/1Socio-Techno-Economic Pathways for Sustainable Urban Energy Development2019-052022-0430万英镑,在研,参加。

  6. 英国工程和自然科学研究委员会,面上项目,EP/R030235/1Resilient Electricity Networks for a productive Grid Architecture (RENGA)2018-052022-0498万英镑,在研,参加。

  7. 英国工程和自然科学研究委员会,面上项目,EP/L019469/1SUPERGEN Energy Storage Hub391万英镑,2014-062019-12,已结题,参加。

  8. 英国工程和自然科学研究委员会,面上项目,EP/K039326/1Whole Systems Energy Modelling Consortium (WholeSEM)2013-072018-01461万英镑,已结题,参加


专著:

  1. Y. Ye; Modeling and analyzing the integration of energy storage and flexible demand resources in deregulated electricity markets; NanjingSoutheast University Press2022.英文专著


期刊论文:

  1. 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, early access.

  2. 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,1-14.

  3. Q. YuanY. Ye*et al, “A novel deep-learning based surrogate modeling of stochastic electric vehicle traffic user equilibrium in low-carbon electricity-transportation nexus,” Applied Energy, early access

  4. H. Cui, Q. Wang, Y. Ye*, et. al, “A Combinational Transfer Learning Framework for Online Transient Stability Prediction,” Sustainable Energy, Grids and Networks, early access.

  5. 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.

  6. 叶宇剑,袁泉,汤奕,.抑制柔性负荷过响应的微网分散式调控参数优化[J/OL].中国电机工程学报:1-13. http://kns.cnki.net/kcms/detail/11.2107.TM.20210629.174 1.015.html.

  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,202246(01)110-119

  8. 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. 2020.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Y. Ye*, D. Qiu, et.al, "Real-Time Autonomous Residential Demand Response Management Based on Twin Delayed Deep Deterministic Policy Gradient Learning", Energies, vol. 14, no. 3, pp. 531, Jan. 2021.

  16. J. Li, Y. Ye*, 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.

  17. 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, vol. 8, no. 2, pp. 734-749, Jan. 2021.

  18. D. Qiu, Y. Ye*, et. al, “Scalable Coordinated Management of Peer-to-Peer Energy Trading: A Multi-Cluster Deep Reinforcement Learning Approach,” Applied Energy, vol. 292, p. 116940, Apr. 2021.

  19. 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.

  20. 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.

  21. 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.

  22. 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.

  23. H. Wang, Q. Wang, Y. Ye, et. al, “Spatial load migration in a power system: concept, potential and prospects,”International Journal of Electrical Power and Energy Systems, Jan. 2022.

  24. W. Sun, Q. Wang, Y. Ye, et. al, “Unified Modelling of Gas and Thermal Inertia for Integrated Energy System and its Application to Multitype Reserve Procurement”, Applied Energy, vol. 305, p. 117963, Jan. 2022.

  25. F. Shuang, J. Chen, Y. Ye, et.al, “A two-stage deep transfer learning for localisation of forced oscillations disturbance source”, International Journal of Electrical Power and Energy Systems, vol. 135, p. 107577, Feb. 2022.

  26. 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.

  27. 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.

  28. 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:

  1. 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%)

  2.  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)

  3. Y. Ye, D. Qiu, et. al, “A Deep Q Network Approach for Optimizing Offering Strategies in Electricity Markets,” Proc. 2nd International Conference on Smart Energy Systems and Technologies (SEST), Porto, Portugal, Sep. 9-11, 2019.

  4. Y. Ye, D. Papadaskalopoulos, et. al, "Strategic capacity withholding by energy storage in electricity markets", Proc. PowerTech Conference 2017, Manchester, UK, Jun. 2017.

  5. 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.

  6. 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.

  7. P. Chen, Y. Ye, J. Hu, et. al, “Dynamic Modeling of Smart Buildings Energy Consumption: A Cyber-Physical Fusion Approach”, Proc. 2021IEEE Sustainable Power and Energy Conference (iSPEC), Nanjing, China, Nov. 25-27, 2021.

  8. H. Wang, Y. Ye, Y. Tang, “Towards Market-Based Integration of Renewable Generation in Power Grids”, Proc. 2021IEEE Sustainable Power and Energy Conference (iSPEC), Nanjing, China, Nov. 25-27, 2021.

  9. Q. Yuan, Y. Ye, Y. Tang, X. Liu and Q. Tian, “Optimal Load Scheduling in Coupled Power and Transportation Networks”, Proc. 2021 IEEE IAS Industrial & Commerical Power System Asia, Chengdu, China, July. 18-21, 2021.

  10. 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.

  11. 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.

  12. J. Li, Y. Ye, et. al, “Incentivizing Peer-to-Peer Energy Sharing Using a Core Tâtonnement Algorithm,” Proc. 2020 IEEE Power & Energy Society General Meeting (GM), Montreal, Canada, 2-6 Aug. 2020.

  13. Q. Yuan, Y. Ye, X. Liu, et. al, "Optimal Load Scheduling in Coupled Power and Transportation Networks," submitted to 2021 IEEE Power & Energy Society General Meeting (GM), under review.

  14. J. Li, Y. Ye, et. al, “Consensus-Based Coordination of Time-Shiftable Flexible Demand,” Proc. 2ndInternational Conference on Smart Energy Systems and Technologies (SEST), Porto, Portugal, Sep. 9-11, 2019.

  15. 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.

  16. 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.

  17. 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.

  18.  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.

  19.  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.

  20. 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.

  21. 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.

专利:

1. 叶宇剑; 袁泉; 汤奕 ; 一种面向含大规模产消者社区的可扩展能量管理协同方法, 2021-11-05, 中国, 202111302186.2 (受理)

2. 叶宇剑; 王卉宇; 汤奕 ; 一种基于近端策略优化的用户实时自治能量管理优化方法, 2021-7-27, 中国, 202110848508.1(受理)

3. 叶宇剑; 袁泉; 汤奕 ; 一种抑制负荷过响应的分散式调控参数优化方法, 2021-2-17, 中国, 202110219581.8 (受理)

4. 叶宇剑; 汤奕; 胡健雄; 吴忠; 陈沛凌 ; 一种基于图论的电量图数据库构建及搜索方法, 2021-12-11, 中国, 202111510601.3 (受理)

5. 叶宇剑; 王卉宇; 汤奕 ; 一种电力市场环境下考虑储能影响的可再生能源规划方法, 2022-2-16, 中国, 202210140149.4 (受理)

6. 叶宇剑; 汤奕; 胡健雄; 吴忠; 陈沛凌 ; 一种基于图卷积神经网络的电量视角推荐方法及系统, 2021-12-08, 中国, 202111491511.4 (受理)

7. 陈沛凌; 叶宇剑; 胡健雄; 王洪儒; 殷勇高; 汤奕; 韩啸 ; 智慧楼宇用电分析的动态建模方法、系统、设备和介质, 2021-12-21, 中国, 202111566675.9(受理)

8. 袁泉; 叶宇剑; 汤奕 ; 图卷积和深度置信网络的电动汽车负荷优化方法, 2021-12-18, 中国, 202111556287.2(受理)

9. 袁泉; 王琦;汤奕; 叶宇剑; 一种电动汽车充电决策的权重量化方法, 2021-12-18, 中国, 202011346880.X(受理)


教学

东南大学:

2020-至今:硕士生、博士生副导师

2021春研究生课程:智能电网(全英文),2021秋本科生课程:智能电网新技术(研讨)

2022春研究生课程:智能电网(全英文),2022春研究生课程:优化理论新技术(全英文)


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