Z
Zhao Yang Dong
Researcher at University of New South Wales
Publications - 930
Citations - 33916
Zhao Yang Dong is an academic researcher from University of New South Wales. The author has contributed to research in topics: Electric power system & Electricity market. The author has an hindex of 77, co-authored 872 publications receiving 23835 citations. Previous affiliations of Zhao Yang Dong include University of Newcastle & University of Queensland.
Papers
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Journal ArticleDOI
Incorporating weather uncertainty in demand forecasts for electricity market planning
TL;DR: An improved methodology for the consideration of weather uncertainty in electricity demand forecasts is presented and case studies based on the Australian national electricity market are used to validate the proposed methodology.
Proceedings Article
Under voltage load shedding utilizing trajectory sensitivity to enhance voltage stability
TL;DR: In this article, the authors proposed an advanced under voltage load shedding based on trajectory sensitivity analysis for voltage stability enhancement, which is a technique based on linearizing a system surrounding a certain trajectory and employs time domain simulations.
Journal ArticleDOI
Convergence of Distributed Accelerated Algorithm Over Unbalanced Directed Networks
TL;DR: By utilizing the small-gain theorem, it is proved that if the maximum step-size is positive and sufficiently small (constrained by a specific upper bound), the proposed algorithm, termed as SGT-FROST, converges geometrically to the optimal solution given that the objective functions are smooth and strongly convex.
Proceedings ArticleDOI
Under voltage load shedding design with modal analysis approach
TL;DR: In this article, a modal analysis based under voltage load shedding method is proposed and detailed case studies are given to validate the proposed approach (5 pages) for power system control subject to large disturbances.
Proceedings ArticleDOI
Demand Side Management Given Distributed Generation and Storage: A Comparison for Different Pricing and Regulation Scenarios
TL;DR: In this article, a day-ahead DSM optimization problem is formulated, which includes demand, generation, storage, and cost models, and a scenario based study for Australian residential households is conducted to reveal the effect of the pricing and regulation on the DSM's performance.