Researcher

Keywords

Fields of Research (FoR)

Electrical energy transmission, networks and systems, Power and Energy Systems Engineering (excl. Renewable Power), Renewable Power and Energy Systems Engineering (excl. Solar Cells), Other Artificial Intelligence

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Biography

Rui Zhang received a B.E. degree from The University of Queensland, Brisbane, QLD, Australia, in 2009 and PhD degree from The University of Newcastle, Newcastle, NSW, Australia, in 2014, both in Electrical Engineering.

She is currently a postdoctoral research associate at the School of Electrical Engineering and Telecommunication, UNSW, Sydney. She is the recipient of the 2022 Australian Research Council Discovery Early Career Researcher...view more

Rui Zhang received a B.E. degree from The University of Queensland, Brisbane, QLD, Australia, in 2009 and PhD degree from The University of Newcastle, Newcastle, NSW, Australia, in 2014, both in Electrical Engineering.

She is currently a postdoctoral research associate at the School of Electrical Engineering and Telecommunication, UNSW, Sydney. She is the recipient of the 2022 Australian Research Council Discovery Early Career Researcher Award(ARC DECRA). Her research focuses on power system stability, planning and control, considering renewable energy integration and energy storage systems through data-driven methods and AI technologies. 

 


My Grants

ARC Discovery Early Career Research Award, " Temporal-Spatial Data Analytics for Exploring Complex Stochastic Power System Stability", 2022. 

UNSW Digital Grid Future Institute Seed Funding project "Coordinated Dynamic Security Defence for Stochastic Electric Power Systems", 2022. 


My Qualifications

PhD in Electrical Engineering (University of Newcastle, Australia)


My Awards

She is named among the World’s Top 2% of Scientists by Stanford in 2024

Rising Stars Women in Engineering, Asian Deans' Forum, 2022

Recipient of Australian Research Council Discovery Early Career Researcher Award (ARC DECRA 2022) in 2022.

University of Newcastle International Postgraduate Research Scholarship (UNIPRS), Sep. 2011-Apr. 2013

1st Runner-up Paper Award, 2011 IET Younger Members Exhibition & Conference, Hong Kong, Jul. 2011


My Research Supervision


Supervision keywords


Areas of supervision

Power system operation, stability and control. 

Data-driven methods and AI-driven methods in power engineering.  

Energy Storage System


Currently supervising

PhD Students research areas:

  • Reinforcement learning for power system control
  • Artificial Intelligence and data processing technology for Energy Internet
  • Residential Consumer Portrait Modelling Based on Multi-dimensional Behaviour Analysis in Smart Grid
  • Real time Data-driven Emergency Control for Power Systems considering Battery Energy Storage Systems

 

 


My Teaching

Teaching Experience: 

 ELEC9781 Special Topics - Energy Storage System(Course Convenor/Lecturer)

 ELEC4612 Power System Analysis(Tutor)

More than 20 Undergraduate/ Postgraduate students mentor

 

 

 

 

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Location

Lab 301 G17 Engineering Building