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— Outstanding Teachers —

ZHAO, Junhua

Title:

Associate Professor

Education Background

PhD (The University of Queensland, Australia)

B.E. (Xi’an Jiaotong University, China)

Research Field
Power System Analysis and Computation; Smart Grid; Data Mining; Artificial Intelligence; Electricity Market
Email

zhaojunhua@cuhk.edu.cn

Biography:


Professor Junhua Zhao received his Bachelor and PhD degrees from Xi’an Jiaotong University, China and The University of Queensland, Australia in 2003 and 2007 respectively. He joined CUHKSZ in 2015 and received the National ‘1000 Talents Program’ Distinguished Young Scholar in 2016. Before joining CUHKSZ, He was a Senior Lecturer and also acted as the Principal Research Scientist of Centre for Intelligent Electricity Networks, the University of Newcastle, Australia. He published more than 120 research papers, which include more than 60 articles on prestigious journals. He received the IEEE PES General Meeting best paper award in 2014, Science and Technology Progress Award (2nd prize) from Hunan Provincial government, China in 2013, and three times of ‘F5000’ Top Articles Award from Ministry of Science and Technology, China. He was previously a member of a Global Smart Grid Federation (GSGF) working group, and a member of a Smart Grid Australia (SGA) working group. He has led or participated in more than 20 important research and industrial projects, which include the ‘Smart Grid, Smart City’ trial program funded by Australian government, two flagship cluster programs funded by Commonwealth Science and Industrial Research Organization (CSIRO), and one Electric Power Research Institute (EPRI) project. He is the editorial board members of JOURNAL OF MODERN POWER SYSTEM AND CLEAN ENERGY, and ELECTRIC POWER COMPONENTS AND SYSTEMS. In 2017, Professor Zhao was rewarded ‘Young Scientist of the Future’ by ADC Forum because of his outstanding contribution to the Australian energy system research.


Academic Publications:


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.