23 citations · 111 across the 21 of their papers we have counts for
26 papers
Resilience Enhancement of Distribution Grids Through a Three-Stage Framework for Scheduling Mobile Energy Storage Systems
Ali Abbasi, Kyri Baker
As high-impact, low-probability disturbances such as extreme weather events increase in frequency, enhancing power grid resilience has become a critical priority. Mobile Energy Sto…
Numerical Comparisons of Linear Power Flow Approximations: Optimality, Feasibility, and Computation Time
Meiyi Li, Yuhan Du, Javad Mohammadi +3
Linear approximations of the AC power flow equations are of great significance for the computational efficiency of large-scale optimal power flow (OPF) problems. Put differently, t…
Gradient-Enhanced Physics-Informed Neural Networks for Power Systems Operational Support
Mostafa Mohammadian, Kyri Baker, Ferdinando Fioretto
The application of deep learning methods to speed up the resolution of challenging power flow problems has recently shown very encouraging results. However, power system dynamics a…
Towards Understanding the Unreasonable Effectiveness of Learning AC-OPF Solutions
My H. Dinh, Ferdinando Fioretto, Mostafa Mohammadian +1
Optimal Power Flow (OPF) is a fundamental problem in power systems. It is computationally challenging and a recent line of research has proposed the use of Deep Neural Networks (DN…
OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets
Trager Joswig-Jones, Kyri Baker, Ahmed S. Zamzam
Increasing levels of renewable generation motivate a growing interest in data-driven approaches for AC optimal power flow (AC OPF) to manage uncertainty; however, a lack of discipl…
GridLearn: Multiagent Reinforcement Learning for Grid-Aware Building Energy Management
Aisling Pigott, Constance Crozier, Kyri Baker +1
Increasing amounts of distributed generation in distribution networks can provide both challenges and opportunities for voltage regulation across the network. Intelligent control o…