3 citations · 5 across the 6 of their papers we have counts for
13 papers
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…
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…
Health-Focused Optimal Power Flow
Logesh Kumar, Parikshit Pareek, Sivakumar Nadarajan +3
In this paper, we propose a novel Health-Focused Optimal Power Flow (HF-OPF) to take into account the equipment health in operational and physical constraints. The health condition…
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…