Dr Rachel Zhang
Lecturer
PhD in Electrical Engineering (University of Newcastle, Australia)
Engineering
Electrical Engineering and Telecommunications
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 Lecturer in the School of Electrical Engineering and Telecommunications at UNSW Sydney. Rui is a recipient of the prestigious Australian Research Council Discovery Early Career Researcher Award (ARC DECRA) in 2022. Her research focuses on power system stability assessment, planning, and control, with particular emphasis on renewable energy integration and energy storage systems. She develops novel data-driven and AI-based methodologies to support the reliable and intelligent operation of future power grids.
E-mail
Location
Lab 301 G17 Engineering Building
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
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.
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 focuses on the stability, resilience, and intelligent operation of modern power systems with high penetration of renewable energy and energy storage. I develop data-driven and AI-based methods for real-time stability assessment and control, and optimal dispatch of distributed energy resources.
Key research areas include:
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Power system stability assessment and control under increasing uncertainty and variability
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Machine learning and reinforcement learning applications for dynamic security analysis and preventive/emergency control
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Battery energy storage systems: state-of-health estimation, coordinated dispatch, and economic optimisation
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Temporal–spatial data analytics for power system stability assessment
My Research Supervision
I am currently supervising the following PhD students (as Primary Supervisor), whose research covers the following areas:
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Real-time data-driven emergency control for power systems considering battery energy storage
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Artificial intelligence and data processing technologies for the energy internet
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Residential consumer modeling based on multi-dimensional behavioural data in smart grids
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Reinforcement learning for power system control
My Teaching
Teaching Experience:
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ELEC9781 Special Topics – AI Applications in Power Systems with Renewable Energy, T2 2025
(Course Developer / Course Convenor / Lecturer) -
ELEC9781 Special Topics – Energy Storage System
(Course Convenor / Lecturer) -
ELEC4612 Power System Analysis
(Tutor)
Supervised more than 30 Undergraduate and Postgraduate students in their thesis projects.
Current Thesis Supervision – Master Students:
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Haoquan Zhang
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Yijie Xu
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Yang Li
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Zhengzhi Lan
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Jianning Cao
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Runze Cao
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Pacharaporn Srithaporn
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Hanwen Gao
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Bingbing Chen
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Guangjun Yin
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Chenyu Ju
Alumni – Bachelor Students:
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Huaiyu Sun
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Guanyu Wang
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Kai Pearson
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Hanwen Zhang
Alumni – Master Students:
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Muhammad M. Qaisar
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Yizhou
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Wenzheng Jiang
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Zixuan Wang
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Qicheng Chen
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Siyuan Deng
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Fanli Ma
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Shanshan Jiang
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Yizhou Hu
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Yushuangying Xie
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Xuanping Zhao
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Yutong Zhao
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Yitao Du
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Hanlin Zheng
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Zhuohao Gong
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Chenyu Li
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Xiaoru Chen
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Fei Ding
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Yuanqing Ma