赵俊华

教授

教育背景

博士(澳大利亚昆士兰大学)
工学学士(中国西安交通大学)

研究领域
电力系统分析与计算、智能电网、数据挖掘、人工智能、电力市场
个人网站
个人简介

赵俊华教授是香港中文大学(深圳)理工学院教授,中新智慧储能联合研究中心执行主任,深圳高等金融研究院能源市场与能源金融实验室主任,深圳人工智能与机器人研究院研究员。他回国前曾担任澳大利亚纽卡斯尔大学智能电网研究中心主任科学家,在澳大利亚有11年的电力行业从业经验。长期从事智能电网、电力市场、低碳转型、人工智能等方面的研究工作。在国际、国内著名期刊和国际会议上发表论文300余篇,其中包括Cell子刊Joule 1篇,Patterns 1篇,Nature子刊Scientific Data 2篇,中国工程院院刊Engineering 1篇,IEEE Transactions收录论文60余篇。发表的论文被国内外引用15000余次,H-index为61(根据Google Scholar统计)。合著英文著作两部。

2023年当选英国工程技术学会会士(IET Fellow)。2023年获评麻省理工科技评论“中国智能计算创新人物”。2021–2023年连续入选Elsevier“中国高被引学者”。2023年获国际金融论坛(IFF)“全球绿色金融奖”。2022年获广东省电力科技杰出贡献奖。2020年获得浙江省自然科学二等奖。2020年获国际期刊Energy Conversion and Economics年度最具影响力论文。2017年获澳大利亚达沃斯论坛(ADC Forum)授予青年科学家奖(Young Scientist of the Future)。2017年获国家科技部“中国百篇最具影响力中文科技期刊论文”奖。2016年获得顶级期刊IEEE Transactions on Smart Grid授予最佳审稿人奖。2014年获得IEEE电力与能源大会(IEEE PES General Meeting)最佳论文奖(Best Paper Award)。两次获得湖南省科技进步二等奖。2020年获深圳特区金融学会重点课题评选二等奖。研究成果在工业界产生了重要影响,担任我国首个省级电力现货市场和首个区域电力现货市场的专家组成员,参与了国内首个跨境碳交易产品的设计。参与开发的多个软件产品先后应用于纽约爱迪生公司、港灯集团、广东省能源集团、中海油、大唐发电等大型能源企业。

招商银行总部特聘能源行业专家。《澳大利亚国家展望报告(Australian National Outlook)》特邀外部专家。IEEE Special Interest Group (SiG) on Active Distribution Grids and Microgrids联合主席。IEEE PES SBLC (Smart Building, Load and Customer) 亚太工作组秘书,国际智能电网联盟(GSGF)“Interfaces of Grid Users/ Focus on EV and Local Storage”专家组成员。担任IEEE Transactions on Network Science and EngineeringEnergy Conversion and Economics等多个国际期刊编委。

学术著作

1. Zhao, J.H., Xu, Y., Luo, F., Dong, Z., & Peng, Y. (2014). Power system fault diagnosis based on history driven differential evolution and stochastic time domain simulation. Information Sciences, 275, 13-29.
2. Yao, W., Zhao, J.H., Wen, F., Xu, Y., Meng, K., Dong, Z., Xue, Y. (2014). A multi-objective collaborative planning strategy for integrated power distribution and electric vehicle charging systems. IEEE Transactions on Power Systems, 29(4), 1811-1821.
3. Zheng, Y., Xu, Y., Meng, K., Zhao, J. H., Qiu, J., & Dong, Z. Y. (2014). Electric vehicle battery charging/swap stations in distribution systems: Comparison study and optimal planning. IEEE Transactions on Power Systems, 29(1), 221-229.
4. J. Qiu, Z. Y. Dong, J. H. Zhao, K. Meng, Y. Zheng, and D. Hill (2014). Low carbon driven expansion planning of the integrated gas and power systems, IEEE Trans. Power Systems.
5. G.B. Wang, J.H. Zhao, F.S. Wen, Y.S. Xue and G. Ledwich (2014). Dispatch Strategy of PHEVs to Mitigate Selected Patterns of Seasonally Varying Outputs from Renewable Generation, IEEE Transactions on Smart Grid.
6. F.J. Luo, J.H. Zhao (*), Z.Y. Dong, X.J. Tong, H.M. Yang, Y.Y. Chen, and H.L. Zhang (2014). Optimal air conditioner load dispatch in southern China region using fuzzy adaptive imperialist competitive algorithm, IEEE Transactions on Smart Grid.
7. Yang, H., Yi, D., Zhao, J.H. (*), & Dong, Z. (2013). Distributed Optimal Dispatch of Virtual Power Plant via Limited Communication. IEEE Transactions on Power Systems, 28(3), 3511-3512.
8. Yao, W., Zhao, J.H., Wen, F., Xue, Y., & Ledwich, G. (2013). A Hierarchical Decomposition Approach for Coordinated Dispatch of Plug-in Electric Vehicles. IEEE Transactions on Power Systems, 28(3), 2768-2778.
9. Yang, H., Chung, C. Y., & Zhao, J.H. (2013). Application of plug-in electric vehicles to frequency regulation based on distributed signal acquisition via limited communication. IEEE Transactions on Power Systems, 28(2), 1017-1026.
10. Yang, H., Yi, J., Zhao, J.H. (*), & Dong, Z. (2013). Extreme learning machine based genetic algorithm and its application in power system economic dispatch. Neurocomputing, 102, 154-162.
11. Zhao, J.H., Wen, F., Dong, Z. Y., Xue, Y., & Wong, K. P. (2012). Optimal dispatch of electric vehicles and wind power using enhanced particle swarm optimization. IEEE Transactions on Industrial Informatics, 8(4), 889-899.
12. Dong, Z. Y., Zhao, J.H., & Hill, D. J. (2012). Numerical simulation for stochastic transient stability assessment. IEEE Transactions on Power Systems, 27(4), 1741-1749.
13. J.H. Zhao, ZY Dong, P. Lindsay and K.P. Wong (2009). Flexible transmission expansion planning with uncertainties in an electricity market, IEEE Trans on Power Systems, 24(1), 479-488.
14. J.H. Zhao, Z.Y. Dong, Z. Xu and K.P. Wong (2008). A Statistical Approach for Interval Forecasting of the Electricity Price, IEEE Trans on Power Systems, 23(2), 267-276.
15. J.H. Zhao, Z.Y. Dong, X. Li and K.P. Wong (2007). A Framework for Electricity Price Spike Analysis with Advanced Data Mining Methods, IEEE Trans on Power Systems, 22(1), 376-385.