2 citations · 4 across the 18 of their papers we have counts for
7 papers · 1 filter
Homotopy-Guided Self-Supervised Learning of Parametric Solutions for AC Optimal Power Flow
Shimiao Li, Aaron Tuor, Draguna Vrabie +2
Learning to optimize (L2O) parametric approximations of AC optimal power flow (AC-OPF) solutions offers the potential for fast, reusable decision-making in real-time power system o…
Voltage-Regulated Sparse Optimization for Proactive Diagnosis of Voltage Collapses
Qinghua Ma, Seyyedali Hosseinalipour, Ming Shi +2
This paper aims to proactively diagnose and manage the voltage collapse risks, i.e., the risk of bus voltages violating the safe operational bounds, which can be caused by extreme…
Frequency-Aware Sparse Optimization for Diagnosing Grid Instabilities and Collapses
Swadesh Vhakta, Denis Osipov, Reetam Sen Biswas +3
This paper aims to proactively diagnose and manage frequency instability risks from a steady-state perspective, without the need for derivative-dependent transient modeling. Specif…
Sparsity-exploiting Gaussian Process for Robust Transient Learning of Power System Dynamics
Tina Gao, Shimiao Li, Lawrence Pileggi
Advances in leveraging Gaussian processes (GP) have enabled learning and inferring dynamic grid behavior from scarce PMU measurements. However, real measurements can be corrupted b…
Cyber-Resilient System Identification for Power Grid through Bayesian Integration
Shimiao Li, Guannan Qu, Bryan Hooi +3
Power grids increasingly need real-time situational awareness under the ever-evolving cyberthreat landscape. Advances in snapshot-based system identification approaches have enable…
Multi-Period Sparse Optimization for Proactive Grid Blackout Diagnosis
Qinghua Ma, Reetam Sen Biswas, Denis Osipov +3
Existing or planned power grids need to evaluate survivability under extreme events, like a number of peak load overloading conditions, which could possibly cause system collapses…
Synergies between Federated Foundation Models and Smart Power Grids
Seyyedali Hosseinalipour, Shimiao Li, Adedoyin Inaolaji +3
The recent emergence of large language models (LLMs) such as GPT-3 has marked a significant paradigm shift in machine learning. Trained on massive corpora of data, these models dem…