人员简介

赵俊华

职务/职称

深圳市大数据研究院智慧城市/交通/物流大数据实验室研究科学家

香港中文大学(深圳)副教授

研究方向

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

电子邮箱

zhaojunhua@cuhk.edu.cn

教育背景

澳大利亚昆士兰大学博士

西安交通大学工学学士

个人介绍

赵俊华博士是香港中文大学(深圳)副教授,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、能源经济、机器学习与人工智能等方面的研究工作。在国际国内著名期刊上发表论文200余篇,其中SCI收录论文超过100篇, IEEE Transactions收录论文50篇。发表的论文被国内外引用7300次,H-index为43(根据Google Scholar统计)。

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);2013年与国内学者合作获得湖南省科技进步二等奖(排名第二);四次获得全国“F5000”精品论文奖。

具有丰富的电力能源行业实践经验,研究成果在工业界产生了重大影响。深度参与了中国首个电力现货市场的规则设计与市场建设。参与开发的三项软件产品已在纽约爱迪生公司、香港电灯公司、广东省能源集团、大唐发电、中海油等大型能源企业获得实际应用。先后主持或参与了包括澳大利亚联邦“智能电网、智能城市”试点项目等在内的重大科技项目30余项,获得总科研经费超过3000万元。

《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;澳大利亚智能电网研究委员会(SGA)“Cyber Physical Security of the Smart Grid”专家组成员;澳大利亚联邦检察官办公室CIPMA(Critical Infrastructure Program for Modelling and Analysis)专家组成员; 深圳人工智能产业协会专家委员会副主席。国际期刊Electric Power Components and Systems 编委;国际期刊Modern Power System and Clean Energy 编委;国际期刊Power System Protection and Control编委;澳大利亚国家研究基金委员会(ARC)评审专家;中国国家自然科学基金委员会评审专家;香港政府研究基金(RGC)评审专家;IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Transactions on Neural Networks and Learning Systems, Applied Energy, IET Generation, Transmission & Distribution等多个国际顶级期刊的审稿人。

代表性论文

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.