Y
Yue Chen
Researcher at The Chinese University of Hong Kong
Publications - 21
Citations - 120
Yue Chen is an academic researcher from The Chinese University of Hong Kong. The author has contributed to research in topics: Computer science & Distributed generation. The author has an hindex of 4, co-authored 19 publications receiving 34 citations. Previous affiliations of Yue Chen include Tsinghua University & National Renewable Energy Laboratory.
Papers
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Journal ArticleDOI
An Energy Sharing Mechanism Achieving the Same Flexibility as Centralized Dispatch
TL;DR: It is proved that the proposed mechanism can achieve the same disutility and flexibility as centralized dispatch, and an effective modified best-response based algorithm for reaching the market equilibrium is developed.
Journal ArticleDOI
Approaching Prosumer Social Optimum via Energy Sharing With Proof of Convergence
TL;DR: In this paper, an energy sharing mechanism is proposed to accommodate prosumers' strategic decision-making on their self-production and demand in the presence of capacity constraints, where prosumers play a generalized Nash game.
Journal ArticleDOI
Learning the Optimal Strategy of Power System Operation With Varying Renewable Generations
TL;DR: A method to learn the optimal strategy from a mixed-integer quadratic program with time-varying parameters is developed, which can model many power system operation problems such as unit commitment and optimal power flow.
Journal ArticleDOI
Combining model-based and model-free methods for stochastic control of distributed energy resources
Yue Chen,Yashen Lin +1 more
TL;DR: In this article, a hierarchical control framework that combines the model-based and model-free methods for stochastic DER control in distribution systems is proposed, where the upper-level scheduler considers a chance-constrained optimal power flow problem (model-based) that schedules DER setpoints to minimize the operational cost and maintain the operating reserve.
Proceedings ArticleDOI
Solving Optimal Power Flow for Distribution Networks with State Estimation Feedback
TL;DR: The numerical results demonstrate that the proposed OPF problems based on the state estimation (SE) feedback for the distribution networks where only a part of the involved system states are physically measured is more robust to large pseudo measurement variability and inherent sensor noise in comparison to the other frameworks without SE feedback.