51 citations · 123 across the 20 of their papers we have counts for
11 papers · 1 filter
A Convergence Predictor Model for Consensus-based Decentralised Energy Markets
Parikshit Pareek, L. P. Mohasha Isuru Sampath, Hung D. Nguyen +1
This letter introduces a convergence prediction model (CPM) for decentralized market clearing mechanisms. The CPM serves as a tool to detect potential cyber-attacks that affect the…
A Gaussian Process-based Price-Amount Curve Construction for Demand Response Provided by Internet Data Centers
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 s…
Gaussian Process-based Approach for Bilevel Optimization in the Power System -- A Critical Load Restoration Case
Yang Liu, Yu Weng, Rufan Yang +2
Bilevel optimization problems can be used to represent the collaborative interaction between a power system and grid-connected entities, called the followers, such as data centers.…
A Framework for Health-informed RUL-constrained Optimal Power Flow with Li-ion Batteries
Jiahang Xie, Yu Weng, Hung D. Nguyen
Battery energy storage systems are widely adopted in grid-connected applications to mitigate the impact of intermittent renewable generations and enhance power system resiliency. D…
A Two-Layer Framework with Battery Temperature Optimal Control and Network Optimal Power Flow
Anshuman Singh, Wang Peng, Hung D. Nguyen
Battery energy storage is an essential component of a microgrid. The working temperature of the battery is an important factor as a high-temperature condition generally increases l…
Gaussian Process Learning-based Probabilistic Optimal Power Flow
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 d…
Non-parametric Probabilistic Load Flow using Gaussian Process Learning
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 uncer…
Probabilistic Robust Small-Signal Stability Framework using Gaussian Process Learning
Parikshit Pareek, Hung D. Nguyen
While most power system small-signal stability assessments rely on the reduced Jacobian, which depends non-linearly on the states, uncertain operating points introduce nontrivial h…
Region of Attraction for Power Systems using Gaussian Process and Converse Lyapunov Function -- Part I: Theoretical Framework and Off-line Study
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 sys…
Inverse Stability Problem and Applications to Renewables Integration
Thanh Long Vu, Hung Dinh Nguyen, Alexandre Megretski +2
In modern power systems, the operating point, at which the demand and supply are balanced, may take different values due to changes in loads and renewable generation levels. Unders…
Robust Stability Assessment in the Presence of Load Dynamics Uncertainty
Hung D. Nguyen, Konstantin Turitsyn
Dynamic response of loads has a significant effect on system stability and directly determines the stability margin of the operating point. Inherent uncertainty and natural variabi…