46 citations · 155 across the 26 of their papers we have counts for
4 papers · 1 filter
PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems
David Biagioni, Xiangyu Zhang, Dylan Wald +4
We present the PowerGridworld software package to provide users with a lightweight, modular, and customizable framework for creating power-systems-focused, multi-agent Gym environm…
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…
Data-Driven Moment-Based Distributionally Robust Chance-Constrained Optimization
Joshua Comden, Ahmed S. Zamzam, Andrey Bernstein
Many stochastic optimization problems include chance constraints that enforce constraint satisfaction with a specific probability; however, solving an optimization problem with cha…
Enhancement of Distribution System State Estimation Using Pruned Physics-Aware Neural Networks
Minh-Quan Tran, Ahmed S. Zamzam, Phuong H. Nguyen
Realizing complete observability in the three-phase distribution system remains a challenge that hinders the implementation of classic state estimation algorithms. In this paper, a…