Dr Rachel Zhang | UNSW Research

Keywords

power systems

power system stability

big data analytics

machine learning

energy storage system

renewable energy

artificial intelligence

smart grids

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

SEO tags

Energy systems analysis

Renewable Energy

Energy storage

Biography

Dr Rui Zhang received the B.E. degree in Electrical Engineering from The University of Queensland, Brisbane, Australia, in 2009, and the PhD degree in Electrical Engineering from The University of Newcastle, Newcastle, Australia, in 2014. She is currently a Scientia Lecturer in the School of Electrical Engineering and Telecommunications at UNSW Sydney. She is also the recipient of the Australian Research Council Discovery Early Career...view more

Dr Zhang leads a research team in the areas of power system stability assessment, operation, planning and control, including renewable energy integration, energy storage systems, and AI applications in power and energy systems. Her research aims to develop data-driven, physics-informed, and artificial intelligence-based methodologies to support the reliable, resilient, and intelligent operation of future power grids.

Her work lies at the intersection of power engineering, data analytics, and intelligent decision-making, with interests spanning power system stability and resilience, renewable-dominated grid operation, battery energy storage systems, and AI-enabled monitoring and control of modern energy systems.

Dr Zhang is a Senior Member of IEEE and currently serves as an Associate Editor for Engineering Applications of Artificial Intelligence (Elsevier). She is also an active reviewer for a number of leading international journals, including IEEE Transactions on Power Systems, IEEE Transactions on Smart Grid, IEEE Transactions on Sustainable Energy, IEEE Transactions on Industrial Informatics, IET Generation, Transmission & Distribution, and Nature Energy, among others.

Prospective students interested in pursuing MPhil or PhD research in power system stability, AI-enabled power and energy systems, renewable integration, and energy storage are warmly encouraged to get in touch. Research Assistant (RA) opportunities may also be available for suitable candidates through ongoing research projects.

My Grants

2025-2026 Involved (CI) in the project 'Revolutionary AI-Enabled Modular Power Portal System for Urban Clean Energy Distribution', TRaCE Lab to Market fund, Australia, 4,191,250 AUD

2025-2026 Lead CI in the project 'Health status estimation and resilient closed-loop supply chain for retired electric vehicle batteries', AEA Ignite round 1, Australia, 334,052 AUD

2022-2025 Sole-CI, ARC Discovery Early Career Research Award, "Temporal-Spatial Data Analytics for Exploring Complex Stochastic Power System Stability". 461,556 AUD

2022 Sole-CI, UNSW Digital Grid Future Institute Seed Funding project "Coordinated Dynamic Security Defence for Stochastic Electric Power Systems", 2022. 50,000 AUD

My Qualifications

PhD in Electrical Engineering, University of Newcastle (UON), Newcastle, Australia
B.E. in Electrical Engineering, University of Queensland (UQ), Brisbane, Australia

My Awards

UNSW ECAN Early Career Academic Excellence Award (Education) in 2025

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

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

My Research Activities

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:

Temporal–spatial data analytics for power system stability
AI-driven methods for power system stability assessment and control
Data analytics for smart grid applications.
Renewable integration and inverter-dominated grid operation
Battery energy storage systems optimization and Battery Health Management

My Research Supervision

Supervision keywords

power systems

smart grids

big data analytics

power system stability

energy storage system

artificial intelligence

smart microgrid

Areas of supervision

Power system stability analysis and control, including transient, voltage, and frequency stability.
AI-driven and data-driven methods for power system operation, planning, and decision-making.
Reinforcement learning and intelligent control techniques for enhancing power system resilience.
Energy storage systems: optimisation, control, and integration with renewable energy.
Battery health estimation, lifecycle modelling, and data analytics for grid-connected storage.

Currently supervising

I am currently supervising the following PhD students (as Primary Supervisor), whose research covers the following areas:

Real-time data-driven emergency control for power systems considering battery energy storage
Artificial intelligence and data processing technologies for the energy internet
Residential consumer modeling based on multi-dimensional behavioural data in smart grids
Reinforcement learning for power system stability control

My Teaching

Teaching Experience:

ELEC9781 Special Topics – AI Applications in Power Systems with Renewable Energy, T2 2025

(Course Developer / Course Convenor / Lecturer)
ELEC9781 Special Topics – Energy Storage System, T2 2024

(Course Convenor / Lecturer)
ELEC4612 Power System Analysis(Tutor)
ELEC3111 Distributed Energy Generation (Lecturer)