个人简介

杨之乐      Zhile (Slerk) Yang      英国贝尔法斯特女王大学博士学位      助理研究员
分别于2010年、2013年分获上海大学电气工程自动化专业学士,控制理论与控制工程硕士, 2013-2017在国家留学基金委资助下赴英国贝尔法斯特女王大学留学,并获电子与电气工程博士学位。2016年9月至2017年7月在女王大学从事博士后研究,2017年9月归国起在中科院深圳先进技术研究院任助理研究员。共发表SCI/EI检索重要期刊及顶级会议论文50余篇,其中IEEE Trans、IET、Elesvier等顶级SCI检索期刊论文20余篇,研究方向为包括启发式优化、神经网络等计算智能算法在能源、电力和先进制造中的应用。

教育背景

  2013.02-2017.03
英国贝尔法斯特女王大学
电子电气工程   博士
  2010.09-2013.01   上海大学
控制理论与控制工程   硕士
2006.09-2010.06   上海大学
电气工程及其自动化   学士

研究方向

主要研究方向为计算智能在能源、电力系统应用,包括基于数据的启发式优化与神经网络建模等计算智能方法,即粒子群优化、生物地理优化、教学优化等仿生启发式优化算法、神经网络多层模型结构快速选择方法,及其在电力系统调度,风能、太阳能等新能源并网,电动汽车充放电调度,网络控制系统,电池充放电策略及状态估计,电网故障诊断,精密运动控制系统中参数优化辨识等能源、电力和智能制造等工业热点领域的应用。

工作经历

  2017.09-今
中国科学院深圳先进技术研究院
助理研究员
  2016.09~2017.07
博士后科研助理,英国贝尔法斯特女王大学
英国工程物理研究理事会 全球性挑战项目及中英重点项目
面向塑造低碳能源未来的综合性方法 、电动汽车智能电网环境友好接入

研究经历

2017.08至今 国家自然科学基金委员会面上项目  参与人
面向间歇性新能源与电动汽车大规模渗透下的电力系统智能优化调度研究(64万元)
• 结合最新启发式算法的电力系统多目标智能优化调度
• 电动汽车结合新能源渗透的协同优化策略研究
2017.01至今 国家自然科学基金委员会青年科学基金项目  参与人
高准确度电网孤岛效应协同检测模型研究 (20万元)
• 智能电网中的大数据应用理论综述;
• 智能电网孤岛效应神经网络模型非线性参数优化方法和模型辨识研究;
2017.01至今 国家自然科学基金委员会面上项目  参与人
面向智能电网多元储能系统的信息综合利用及自学习研究(16万元)
• 锂电池储能系统温度和状态估计非线性模型参数优化与辨识;
• 含锂电池和压缩空气储能系统的最优充放电策略优化;
2017.02至今 新能源电力系统国家重点实验室(华北电力大学)开放课题  参与人
面向新能源消纳的多元异构储能系统优化调度(5万元)
• 含锂电池的异构储能系统内部充放电优化调度;
• 含锂电池和锌镍液流电池的异构储能系统接入的智能电网调度策略优化;
2013.02 ~ 2017.07 英国工程物理研究理事会/国家自然科学基金委 重点项目  参与人
电动汽车智能电网环境友好接入 (100万英镑)
• 面向智能电网经济调度和机组组合模型,提出基于启发式优化算法的大规模电动汽车接入的集成调度优化策略;
• 将电动汽车与大规模间歇性风能和太阳能的新能源系统结合,提出电网调度经济性与环境性的目标,及启发优化调度的混合优化策略;
• 提出基于神经网络的电池非线性电压-电流模型和状态估计模型;
• 基于电池内部温度模型建立电动汽车电池充放电策略;
2011.09~2013.09 英国工程物理研究理事会重点项目  参与人
可持续能源与建筑环境的中英科学桥项目 (230万英镑)
• 提出基于启发式优化方法的异构网络最优控制器;
• 开发基于工业异构网络协议的异构网络测控平台;
• 协助参与中国国际工业博览会获创新奖;
2010.09~2013.01 国家863计划课题  参与人
有线/无线异构工业通信网络集成技术 (77万人民币)
• 基于C++平台开发工业通信OPC服务器;
• 工业异构网络实时系统开发,包括Modbus-TCP/RTU, Profibus-DP, EPA 及工业无线网络的嵌入式软件开发;
• 发表软件著作权一项;
2011.03~2012.12 宝钢集团工业技术研究院横向课题  参与人
工业无线网络测控系统 (51万人民币)
• 开发工业通信节点嵌入式软件通信协议;
• 工业通信网络协议实时性分析与测试,包括 IEEE 802.15.4a无线协议, 改进Zigbee协议和Modbus-TCP协议;
• 调试工业通信软件在企业获得成功应用;
• 发表软件著作权一项;

教学经历

2011.09 ~ 至今 在上海大学、贝尔法斯特女王大学期间,指导本科、硕士、博士生十余人
2013.09 ~ 2016.12 实验助教,贝尔法斯特女王大学
• 包括控制与电路专业相关的五门主干课程;
• 英文讲授和辅导相关课程超过200小时;
• 指导本科和硕士生进行实验平台设置和实验实施;
• 课程相关答疑和习题辅导;
2009.03 ~2011.02 课程助教,上海大学
• 控制系统技术与网络控制系统两门课程;
• 协助教授进行课程答疑与习题评判;
• 本科生学生导师和课程导师

学术兼职

2017.01~2017.09 2017生命系统建模和可持续能源与环境大会(LSMS&ICSEE2017)  秘书长
2015.09~2016.09 2016 英国国际控制大会(UKACC2016)秘书长
2016.03~2016.09 2016中英“塑造低碳能源”国际论坛秘书
2012.08~2012.10 2012亚洲仿真大会志愿者主席
2013.05~2015.02 国际电子电气工程师协会贝尔法斯特女王大学学生分会及三个技术分会 (PES,SMC,CIS) 创始人.
2013.05~2016.12 国际电子电气工程师协会学生会员,三个技术分会(PES,SMC,CIS)会员.
2017.07~至今 Springers 旗下Lecture Notes series: Communications in Computer and Information Science专刊客座编辑.
2014.09~至今 20余个国际顶级和知名SCI期刊审稿人: IEEE Transactions on Neural Networks and Learning Systems, Energy, Applied Energy, Energy Conversion and management, Renewable and Sustainable Energy Reviews, Electric Power and Energy System, Neurocomputing, Measurement, Transactions of institute of measurement and control, Energies, Control engineering practice, Modern Power systems and Clean Energy等.
2014.09~至今 20余个国际旗舰或知名会议审稿人: CEC2016, IJCNN 2015, IJCNN2016, ICIC2014, LSMS2014, BlackSeaCom 2015, ICIC2015, FCTA2015, IFAC-SYSID2015, IJCNN2015, VPPC2015, CDC2015, BlackSeeCom2016, CONTROL2016, ICIC2016, WCICA2016, LSMS&ICSEE 2017 等.
2012.08~至今 在IEEE Congress on Evolutionary Computation (CEC), International Conference on Intelligent Computing等国际会议或学术论坛上做大会、口头和墙报报告20余次.

社会兼职

2017.03~至今 英国女王大学国际推广大使
2015.10~至今 上海大学全英校友会秘书长
2014.09~2017.03 北爱尔兰华人联合会秘书长、主席
2015.11~2016.11 北爱尔兰少数民族委员会常务委员
2013.09~2015.06 女王大学中国学生学者联合会主席
2014.06~2015.06 女王大学电子电气学院研究协会常务委员
2011.09~2012.12 上海大学研究生联合会副主席
2006.09~2013.01 上海大学武术协会(上海市十佳、全国百佳社团)创始主席

荣誉与获奖

2017.09 生命系统建模与可持续能源与环境大会最佳论文奖
2017.07 Modern Power System and Clean Energy (JCR 3区)最高引用奖
2016.07 国际电子电气工程师协会计算智能分会优秀代表旅行奖学金
2014.10 生命系统建模与可持续能源与环境大会最佳论文奖
2014.09 国际电子电气工程师协会能源电力分会全球学生领袖旅行奖学金
2014.08 国际电子电气工程师协会欧洲及中东地区全球学生领袖旅行奖学金
2014.07 女王大学能源电力与控制组旅行奖学金
2013.02 英国工程物理研究理事会国际博士生奖学金
2012.09 上海大学研究生十佳精神文明标兵
2012.09 国家留学基金委高水平大学公派博士生奖学金
2012.11 上海大学研究生学术之星
2012.10 上海大学自仪奖学金
2010.10 上海世博会杰出志愿者
2009.11 上海大学十佳优秀学生标兵第一名
2009.10 上海市奖学金
2008.10 国家奖学金
2006.05 河南省三好学生
2005.05 郑州市优秀学生干部

发表论文与著作

图书章节

1. Z. Yang, K. Li, Control and Optimization for Integration of Plug-in Vehicles in Smart Grid, IET Book on Communication, Control and Security Challenges for the Smart Grid, Chapter 11, ISBN: 978-1-78561-142-1.;

2. K. Li, Y. Xue, S. Cui, Q. Niu, Z. Yang, P. Luk, Advanced Computational Methods in Energy, Power, Electric Vehicles and Their Integrations. International Conference on Life System Modeling and Simulation, and International Conference on Intelligent Computing for Sustainable Energy and Environment, Proceedings, Part III, Communications in Computer and Information Sciences, Vol. 763. Springer

 

期刊论文

3. L. Li, Y. Liu, Z. Yang, X. Yang, K. Li, A mean-square error constrained approach to robust stochastic iterative learning control, IET Control Theory & Applications, accepted (SCI, IF: 2.536, JCR 2区);

4. H. Ma, D. Simon, P. Siarry, Z. Yang, M. Fei, Biogeography-Based Optimization: A 10-Year Review, IEEE Transactions on Emerging Topics in Computational Intelligence, 2017, 10:391-407;

5. W. Liu, and Z. Yang*, Kexin Bi, Forecasting the Acquisition of University Spin-outs: An RBF Neural Network Approach , Complexity, accepted (SCI, IF: 4.621, JCR 1区);

6. C. Li, H. Wu, Z. Yang*, Y. Wang, Z. Sun, SHLNN based Robust Control and Tracking for Hypersonic Vehicle under Parameter Uncertainty, Complexity, accepted (SCI, IF: 4.621, JCR 1区);

7. Z. Yang, K. Li, Q. Niu, Y. Xue, A novel parallel-series hybrid meta-heuristic method for solving a hybrid unit commitment problem, Knowledge-Based Systems, 2017, 134:13-30 (SCI, IF: 4.529, JCR 1区);

8. H. Ma, Z. Yang* , P. You, M. Fei, Multi-objective Biogeography-based Optimization for Dynamic Economic Emission Load Dispatch Considering Plug-in Electric Vehicles Charging, Energy, 2017, Vol. 135:101-111 (SCI, IF: 4.520, JCR 1区);

9. Z. Yang, K. Li, Q. Niu, Y. Xue, A comprehensive study of economic unit commitment of power systems integrating various renewable generations and plug-in electric vehicles, Energy Conversion and Management, 2017, 132: 460-481 (SCI, IF: 5.589, JCR 1区);

10. X. Li, K. Li, Z. Yang and C. K. Wong, A Novel RBF Neural Model for Single Flow Zinc Nickel Batteries, Communications in Computer and Information Science, Vol.763, 386-395, 2017 (EI源刊);

11. H. Ma, K. Liu and Z. Yang, Optimal Battery Charging Strategy Based on Complex System Optimization, Communications in Computer and Information Science, Vol.763, 371-378, 2017 (EI源刊);

12. F. Song, Y. Liu, X. Yang, Z. Yang and P. He, Iterative Learning Identification with Bias Compensation for Stochastic Linear Time-Varying Systems, Communications in Computer and Information Science, Vol.762, 231-239, 2017 (EI源刊);

13. Z. Yang, Z. Yang*, K. Li, W. Naeem, K. Liu, Heuristic based norm-optimal terminal iterative learning control for reheating process, Communications in Computer and Information Science, Vol.762, 262-271, 2017 (EI源刊);

14. K. Liu, K. Li, Z. Yang, C. Zhang, J. Deng, An advanced Lithium-ion battery optimal charging strategy, Electrochimica Acta, 2017, Vol. 225, 330-344 (SCI, IF: 4.798, JCR 1区);

15. T. Cheng, M. Chen, P. J. Fleming, Z. Yang, S. Gan, A novel hybrid teaching learning based multi-objective particle swarm optimization and its application in optimal placement of distributed generation, Neurocomputing, 2017, 222, 12-25 (SCI, IF: 3.317, JCR 1区);

16. H. Ma, M. Fei, Z. Yang. Biogeography-based optimization for identifying promising compounds in chemical process. Neurocomputing, 2016, 174: 494-499 (SCI, IF: 3.317, JCR 1区);

17. J. Yan, K. Li, E. Bai, Z. Yang, A. Foley, Time series wind power forecasting based on variant Gaussian Process and TLBO, Neurocomputing, 2016, 189:135–144 (SCI, IF: 3.317, JCR 1区);

18. W. Liu, X. Xu, Z. Yang, J. Zhao and J. Xing, Impacts of FDI Renewable Energy Technology Spillover on China's Energy Industry Performance, Sustainability, 2016, 8, 846 (SCI,SSCI双引, IF: 1.789, JCR 3区);

19. Y. Liu, Z. Chen, Z. Yang, K. Li, J. Tan, An Inline Surface Measurement Method for Membrane Mirror Fabrication Using Two-stage Trained Zernike Polynomials and Elitist Teaching-Learning Based Optimization, Measurement Science and Technology, 2016, 27(12): 124005 (SCI, IF: 1.585, JCR 3区);

20. Z. Yang, K. Li, A. Foley, Computational Scheduling Methods for Integrating Plug-in Electric Vehicles in the Power System: A Review, Renewable and Sustainable Energy Reviews, 2015, 51: 396-416 (SCI, IF: 8.050, JCR 1区);

21. Y. Guo, K. Li, Z. Yang, J. Deng, D. Laverty, A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring, Electric Power Systems Research, 2015, 127: 197-205 (SCI, IF: 2.688, JCR 2区);

22. Z. Sun, K. Li, Z. Yang, Q. Niu, A. Foley , Impact of Electric Vehicles on a Carbon Constrained Power System - A post 2020 case study, Journal of Power and Energy Engineering, 2015, 3: 114-122 (EI源刊);

23. L. Zhang, Q. Niu, Z. Yang and Kang Li, Integration of Electric Vehicles Charging in Unit Commitment, International Journal of Computer Science and Electronics Engineering, 2015, Vol.3, Iss.1, pp 22-27 (EI源刊);

24. Z. Yang, Kang Li, Yuanjun Guo, A New Compact Teaching-Learning-Based Optimization Method, Lecture Notes in Computer Science, Volume 8589, 2014, pp 717-726 (EI源刊);

25. Z. Yang, K. Li, Q. Niu, Y. Xue, A. Foley. A Self-Learning Teaching-Learning Based Optimization for Dynamic Economic/Environmental Dispatch Considering Multiple Plug-in Electric Vehicle Loads. Journal of Modern Power System and Clean Energy, 2014, 2(4): 298-307 (SCI, IF: 1.207, JCR 3区,期刊最高引用奖) ;

26. J. Yan, Z. Yang, K. Li and Y. Xue, A Variant Gaussian Process for Short-term Wind Power Forecasting Based on TLBO, Communications in Computer and Information Science, Vol. 463, 2014, pp 165-174 (EI源刊,最佳论文奖);

27. H. Ma, M. Fei, Z. Yang, H. Wang, Wireless networked learning control system based on Kalman filter and biogeography-based optimization method. Transactions of the Institute of Measurement and Control, 2014, Vol. 36(2) 224–236 (SCI, IF: 1.049, JCR 4区);

28. Z. Yang, M. Fei, W. Hou, B. Wang, The Design and Simulation of a Two-Layer Network Protocol for Industrial Wireless Monitoring and Control System, Communications in Computer and Information Science, Volume 323, 2012, pp 405-413 (EI源刊);

29. 杨之乐, 郑学理, 苏伟, 费敏锐, 付敬奇, 工业无线网络测控系统OPC数据服务器的设计实现, 计算机测量与控制, 2013. Vol 21 (04), pp 865-869 (中文核心)

30. 杨之乐, 王秉臣, 费敏锐, 姚奇, 侯维岩, 基于令牌环的两层工业无线测控网络系统的设计与实现, 仪表技术, 2011.10

31. 吴帆, 杨之乐, 林小玲, 韩正之, 一种嵌入式无线车辆信息采集系统设计, 传感器与微系统, 2013, Vol. 32(02), pp 116-118 (中文核心)

32. 杨睿昕, 王任杰, 林小玲, 杨之乐, 基于无线磁阻传感器的车辆信息采集系统研究与实现, 仪表技术, 2011, Vol. 11, pp 23-26

 

会议论文

1. Y. Liu, Y. Guo, Z. Yang, J. Hu, G. Lu and Y, Wang, Power System Transmission Line Tripping Analysis using a Big Data platform with 3D visualization, IEEE Symposium Series on Computational Intelligence (SSCI), 2017, accepted (EI);

2. X. Li, K. Li and Z. Yang, Teaching-Learning-Feedback-Based Optimization, International Conference on Swarm Intelligence (ICSI’2017), Advances in Swarm Intelligence, 71-79 (EI);

3. X. Li, C. K Wong and Z. Yang, A Novel Flowrate Control Method for Single Flow Zinc/Nickel Battery, International Conference for Students on Applied Engineering (ICSAE 2016). IEEE 2016: 30-35 (EI);

4. Z. Yang, K. Li, X. Xu, A Hybrid Meta-heuristic Method for Unit Commitment Considering Flexible Charging and Discharging of Plug-in Electric Vehicles, in 2016 IEEE Congress on Evolutionary Computation (CEC), IEEE, 2016: 1-8 (EI);

5. K. Liu, K. Li, Z. Yang, C. Zhang, J. Deng, Battery optimal charging strategy for a coupled thermoelectric model, in 2016 IEEE Congress on Evolutionary Computation (CEC) , 2016: 1-8 (EI);

6. T. Cheng, M. Chen, P. J. Fleming, Z. Yang and S. Gan, An Effective PSO-TLBO Algorithm for multi-objective Optimization, in 2016 IEEE Congress on Evolutionary Computation (CEC) , 2016: 1-8 (EI);

7. L. Zhang, K. Li, Z. Yang, Z. Yang and Q. Wang TRIZ Based Teaching Strategy for Wind Turbine Control, 11th International Conference on Control (Control2016), IEEE, 2016: 1-8;

8. H. Ma, Z. Yang, P. You and M. Fei, Complex System Optimization for Economic Emission Load Dispatch, 11th International Conference on Control (Control2016), IEEE, 2016: 1-8 (EI);

9. Z. Yang, K. Li, L. Zhang, Binary Teaching-Learning Based Optimization for Power System Unit Commitment, 11th International Conference on Control (Control2016), IEEE, 2016: 1-8 (EI);

10. Z. Yang, K. Li, Q. Niu, A. Foley, Unit Commitment Considering Multiple Charging and Discharging Scenarios of Plug-in Electric Vehicles, in International Joint Conference on Neural Networks (IJCNN), IEEE, 2015: 1-8 (EI);

11. Z. Yang, K. Li, A. Foley, and C. Zhang, Optimal scheduling methods to integrate plug-in electric vehicles with the power system: a review, in Proceedings of the 19th world congress of the International Federation of Automatic Control (IFAC’14), Cape Town, South Africa. 2014: 24-29 (EI);

12. Z. Yang, K. Li, A. Foley, and C. Zhang, A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles, in Evolutionary Computation (CEC), 2014 IEEE Congress on. IEEE, 2014: 2685-2691 (EI);

13. Z. Yang, K. Li, Q. Niu, C. Zhang, A. Foley, Non-convex Dynamic Economic /Environmental Dispatch with Plug-in Electric Vehicle Loads, in IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG), 2014. IEEE, 2014: 1-7 (EI);

14. C. Zhang, Z. Yang, and K. Li, Modeling of electric vehicle batteries using rbf neural networks, in The 2nd International Conference on Computing, Management and Telecommunications. IEEE, 2014, 116-121(EI);

15. C. Zhang, K. Li, S. Mcloone, and Z. Yang, Battery modelling methods for electric vehicles -a review, in 13th European Control Conference (ECC). IEEE, 2014, 2673-2678 (EI);

16. C. Zhang, K. Li, Z. Yang, L. Pei, and C. Zhu, A new battery modelling method based on simulation error minimization, in IEEE Power and Energy Society General Meeting 2014. 1-6 (EI);

 

软件著作权

17. 杨之乐,郑学理,费敏锐,付敬奇,工业无线故障诊断系统OPC数据管理软件,登记号:2012SR113117

18. 郑学理,杨之乐,付敬奇,费敏锐,面向冶金工业的无线状态监测系统数据管理软件,登记号:2012SR085922