Qut Phd Scholarship: Data-Driven Power System Stability And Strength Analysis

QUT is a major Australian university with a global outlook and a 'real world' focus. We are an ambitious and collaborative institution that seeks to equip our students and graduates with the skills they will need in an increasingly disrupted and challenged world.

The School of Electrical Engineering and Robotics (EER) aims to improve how we understand and take care of the world we live in through sustainable energy solutions and intelligent technology. 

We focus on high-quality, cross-disciplinary research in power engineering, particularly focusing on renewable energy integration, power system stability and AI applications in power systems.

The successful PhD candidates will work in an ARC-funded project supervised by Dr Yuchen Zhang who is an ARC DECRA Fellow and a lecturer in Power Engineering at QUT. He is an internationally recognised researcher in interdisciplinary areas across power engineering and AI, with one book, over 30 papers in high-quality JCR Q1 journals and one best paper award. He is committed to providing mentorship and support to the PhD candidates and will work closely with them to ensure their success and excellence in research.

About the project

Project topic: Data-driven wide-area power system stability and strength monitoring under weak grid conditions

Project summary: This project aims to investigate and evolve the power system stability and strength assessment framework to suit weak electricity grids with substantial renewable sources. It expects to develop a digitalized approach where comprehensive metric indices are estimated by an innovative data-driven system to realize real-time wide-area power system stability and strength assessment under weak grid conditions. Advanced methods will also be developed to bridge the gap between data science and energy system applications. The new suite of next-gen metrics and data-driven techniques will offer the world’s most innovative renewable energy products with desired grid support capability and low system strength operability, that would smooth the transition towards low-carbon electricity future.

Applicants need to be able to:

• meet QUT’s admission criteria for a PhD degree. Expected degree completion/award by July 2024 can be considered.
• be able to commit to full-time, internal enrolment, with commencement in 2025.

In addition, the ideal applicant will possess or be able to demonstrate:

• strong background the following topics (at least one):
  • power system dynamic simulation and analysis
  • grid integration of renewable energy sources
  • power converter/inverter for renewable energy sources
  • AI applications in engineering areas
• additional background or experience in machine learning, data analytics, and other computer science areas would be an advantage
• experience in power system simulation software, such as PSS/E, PSCAD, DIgSILENT, and PowerWorld
• proficiency in programming languages such as MATLAB and Python
• a demonstrated publication record (or potential) in peer-reviewed conferences or journals would be viewed as advantageous
• ability to work independently and as part of a team, managing multiple tasks and priorities effectively, and strong attention to detail
• well-developed written and oral communication skills for presenting research findings and collaborating with interdisciplinary teams.

14 June 2024

QUT - Doctor of Philosophy

QUT - Support for your research journey

Please send a cover letter, your CV and your academic transcripts to *************@qut.edu.au 

The cover letter should highlight your qualifications, research interests and why you are interested in the project.

Only shortlisted candidates will be contacted for an interview.