Dr Yuchen Zhang
Faculty of Engineering,
School of Electrical Engineering & Robotics
Biography
Yuchen Zhang joined QUT as a Lecturer in School of Electricial Engineering and Robotics in 2024. He received his Bachelor of Engineering degree, Bachelor of Commerce degree, and PhD degree in Electrical Engineering from the University of New South Wales (UNSW), Australia in 2013, 2013 and 2018, respectively. Following his PhD, he became a research associate at UNSW from 2018 to 2021, taking key roles in ARC Research Hub for Integrated Energy Storage Solutions. He then received the ARC Discovery Early Career Researcher Award (DECRA) and became a DECRA Fellow from 2022 to 2023. He also worked as a teaching-focused lecturer at Macquarie University, Australia in 2019.He has worked collaboratively with researchers and research institutes in US, Canada, Singapore, and Hong Kong. He has secured industry grants and worked in several industry-funded projects related to renewable energy, power systems, and maritime services in Australia. He is a key member in drafting IEEE P2781 Standard “Guide for Load Modelling and Simulations for Power Systems”.
He has conducted research in interdisciplinary areas across power engineering and artificial intelligence. His research interests include:
- Power system stability assessment and control
- Grid integration of renewable energy resources
- Wind farm planning, operation, and maintenance
- Data-driven system development
- Smart campus and smart city
- AI applications in power engineering
Personal details
Positions
- Lecturer
Faculty of Engineering,
School of Electrical Engineering & Robotics
Keywords
Power System Stability, Renewable Integration, Wind Farm Planning, Smart Grid, Smart City, Artificial Intelligence Applications
Research field
Electrical and Electronic Engineering
Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008
Qualifications
- PhD in Electrical Engineering (University of New South Wales)
Professional memberships and associations
IEEE Member
Publications
- Zuo, T., Zhang, Y., Xie, X., Meng, K., Tong, Z., Dong, Z. & Jia, Y. (2023). A Review of Optimization Technologies for Large-Scale Wind Farm Planning With Practical and Prospective Concerns. IEEE Transactions on Industrial Informatics, 19(7), 7862–7875. https://eprints.qut.edu.au/245885
- Zhang, Y., Liu, J., Xu, Y. & Dong, Z. (2023). An athlete-referee dual learning system for real-time optimization with large-scale complex constraints. Knowledge-Based Systems, 271. https://eprints.qut.edu.au/245879
- Liu, J., Zhang, Y., Meng, K., Dong, Z., Xu, Y. & Han, S. (2022). Real-time emergency load shedding for power system transient stability control: A risk-averse deep learning method. Applied Energy, 307. https://eprints.qut.edu.au/245884
- Zuo, T., Zhang, Y., Meng, K., Tong, Z., Dong, Z. & Fu, Y. (2021). A Two-Layer Hybrid Optimization Approach for Large-Scale Offshore Wind Farm Collector System Planning. IEEE Transactions on Industrial Informatics, 17(11), 7433–7444. https://eprints.qut.edu.au/245887
- Zuo, T., Zhang, Y., Meng, K., Tong, Z., Dong, Z. & Fu, Y. (2021). Collector System Topology Design for Offshore Wind Farm's Repowering and Expansion. IEEE Transactions on Sustainable Energy, 12(2), 847–859. https://eprints.qut.edu.au/245836
- Zhang, Y., Dong, Z., Yip, C. & Swift, S. (2020). Smart campus: a user case study in Hong Kong. IET Smart Cities, 2(3), 146–154. https://eprints.qut.edu.au/245883
- Zhang, Y., Xu, Y., Dong, Z. & Zhang, R. (2019). A Hierarchical Self-Adaptive Data-Analytics Method for Real-Time Power System Short-Term Voltage Stability Assessment. IEEE Transactions on Industrial Informatics, 15(1), 74–84. https://eprints.qut.edu.au/245896
- Zhang, Y., Xu, Y., Zhang, R. & Dong, Z. (2019). A Missing-Data Tolerant Method for Data-Driven Short-Term Voltage Stability Assessment of Power Systems. IEEE Transactions on Smart Grid, 10(5), 5663–5674. https://eprints.qut.edu.au/245894
- Zhang, Y., Xu, Y., Dong, Z. & Zhang, P. (2019). Real-time assessment of fault-induced delayed voltage recovery: A probabilistic self-adaptive data-driven method. IEEE Transactions on Smart Grid, 10(3), 2485–2494. https://eprints.qut.edu.au/245893
- Zhang, Y., Xu, Y., Dong, Z., Xu, Z. & Wong, K. (2017). Intelligent Early Warning of Power System Dynamic Insecurity Risk: Toward Optimal Accuracy-Earliness Tradeoff. IEEE Transactions on Industrial Informatics, 13(5), 2544–2554. https://eprints.qut.edu.au/245892
QUT ePrints
For more publications by Yuchen, explore their research in QUT ePrints (our digital repository).
Awards
- Type
- Academic Honours, Prestigious Awards or Prizes
- Reference year
- 2020
- Details
- 2020 Best Paper Award for IET Smart Cities: “Smart campus: definition, framework, technologies, and services”, vol. 2, no. 1, March 2020
Selected research projects
- Title
- Data-driven Wide-area System Strength Monitoring under Weak Grid Conditions
- Primary fund type
- CAT 1 - Australian Competitive Grant
- Project ID
- DE220100044
- Start year
- 2024
- Keywords
- electricity grid; renewable energy; low carbon
Projects listed above are funded by Australian Competitive Grants. Projects funded from other sources are not listed due to confidentiality agreements.
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