no code implementations • 18 Aug 2023 • Parikshit Pareek, L. P. Mohasha Isuru Sampath, Hung D. Nguyen, Eddy Y. S. Foo
This letter introduces a convergence prediction model (CPM) for decentralized market clearing mechanisms.
no code implementations • 2 Dec 2020 • Yang Liu, Hung D. Nguyen
For a Demand Response (DR) program with internet data centers (IDC), the Price-Amount curve that estimates how the potential DR amount depends on the DR price determined by power systems is crucial.
no code implementations • 2 Dec 2020 • Yang Liu, Yu Weng, Rufan Yang, Quoc-Tuan Tran, Hung D. Nguyen
Then the two layers in the bilevel problem can be solved separately by the power system and its followers.
no code implementations • 16 Apr 2020 • Parikshit Pareek, Hung D. Nguyen
In this letter, we present a novel Gaussian Process Learning-based Probabilistic Optimal Power Flow (GP-POPF) for solving POPF under renewable and load uncertainties of arbitrary distribution.
no code implementations • 8 Nov 2019 • Parikshit Pareek, Chuan Wang, Hung D. Nguyen
In this work, we propose a non-parametric probabilistic load flow (NP-PLF) technique based on the Gaussian Process (GP) learning to understand the power system behavior under uncertainty for better operational decisions.
1 code implementation • 9 Jun 2019 • Chao Zhai, Hung D. Nguyen
This paper introduces a novel framework to construct the region of attraction (ROA) of a power system centered around a stable equilibrium by using stable state trajectories of system dynamics.