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X-ORIGINAL-URL:https://ece.hku.hk
X-WR-CALDESC:Events for Department of Electrical and Computer Engineering (HKUECE) 電機與計算機工程系
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TZID:Asia/Hong_Kong
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TZOFFSETFROM:+0800
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DTSTART:20240101T000000
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DTSTART;TZID=Asia/Hong_Kong:20250814T160000
DTEND;TZID=Asia/Hong_Kong:20250814T173000
DTSTAMP:20260509T210653
CREATED:20250813T012141Z
LAST-MODIFIED:20250813T013434Z
UID:113006-1755187200-1755192600@ece.hku.hk
SUMMARY:Seminar on Voltage Stability Constrained Power System Optimization: A Constraint-learning Method
DESCRIPTION:Abstract\nHigh penetration of renewable energy poses severe challenges to power system voltage stability due to weakened voltage and reactive power support\, complex voltage stability mechanisms\, and highly diversified operation states. Traditional control strategies predefined based on limited operation states fail to maintain the required voltage stability margin. This report presents a constraint-learning-based framework for embedding accurate and efficient voltage stability constraints into power system optimization to improve voltage stability of the optimization results. The proposed framework represents the inherently nonlinear and nonconvex voltage stability constraints using multiple convex polyhedrons (MCPH). The learned constraints are linear\, sparse\, and embeddable in mixed-integer linear programming (MILP) formulations. Case studies demonstrate that integrating MCPH constraints into voltage stability constrained unit commitment improves voltage stability margin with reduced computational burden. Furthermore\, the framework is extended to generation expansion planning\, where physical ensemble constraint learning captures converter-driven stability requirements across diverse generation mix scenarios. The results confirm that the proposed approach effectively balances stability enhancement\, solution efficiency\, and scalability for high-renewable\, stability-constrained power system optimization. \nSpeaker\nMr. Hongyang Jia\nTsinghua University \nSpeaker’s Biography\nHongyang Jia received the B.S. degree in electrical engineering in 2021 from Tsinghua University\, Beijing\, China\, where he is currently pursuing the Ph.D. degree in Electrical Engineering under the supervision of Associate Prof. Ning Zhang. He was a Visiting Ph.D. Student at Imperial College London (Aug. 2024 – Feb. 2025) under Associate Prof. Fei Teng. His research interests center on trustworthy machine learning for science and engineering\, with specific applications in power system optimization under voltage stability constraints\, data-driven security/stability rule extraction and embedding\, and power system voltage stability assessment. \nOrganiser\nProf. Wang Yi \nDepartment of Electrical and Electronic Engineering\,\nThe University of Hong Kong \nAll are welcome!
URL:https://ece.hku.hk/events/20250814-1/
LOCATION:Room CB-601J\, 6/F\, Chow Yei Ching Building\, The University of Hong Kong
CATEGORIES:Highlights,Seminar
ATTACH;FMTTYPE=application/pdf:https://ece.hku.hk/wp-content/uploads/2025/08/August-14-2025-1-Web-banner.pdf
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