46 citations · 155 across the 26 of their papers we have counts for
11 papers · 1 filter
Unsupervised Learning for Equitable DER Control
Zhenyi Yuan, Guido Cavraro, Ahmed S. Zamzam +1
In the context of managing distributed energy resources (DERs) within distribution networks (DNs), this work focuses on the task of developing local controllers. We propose an unsu…
Equitable Networked Microgrid Topology Reconfiguration for Wildfire Risk Mitigation
Yuqi Zhou, Ahmed Zamzam, Andrey Bernstein
The increasing number of wildfires in recent years consistently challenges the safe and reliable operations of power systems. To prevent power lines and other electrical components…
Solving Decision-Dependent Games by Learning from Feedback
Killian Wood, Ahmed Zamzam, Emiliano Dall'Anese
This paper tackles the problem of solving stochastic optimization problems with a decision-dependent distribution in the setting of stochastic strongly-monotone games and when the…
Managing Wildfire Risk and Promoting Equity through Optimal Configuration of Networked Microgrids
Sofia Taylor, Gabriela Setyawan, Bai Cui +2
As climate change increases the risk of large-scale wildfires, wildfire ignitions from electric power lines are a growing concern. To mitigate the wildfire ignition risk, many elec…
Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning
Daniel Tabas, Ahmed S. Zamzam, Baosen Zhang
Constrained multiagent reinforcement learning (C-MARL) is gaining importance as MARL algorithms find new applications in real-world systems ranging from energy systems to drone swa…
Enabling Grid-Aware Market Participation of Aggregate Flexible Resources
Bai Cui, Ahmed Zamzam, Andrey Bernstein
Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. With…
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…
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…
Model-Free State Estimation Using Low-Rank Canonical Polyadic Decomposition
Ahmed S. Zamzam, Yajing Liu, Andrey Bernstein
As electric grids experience high penetration levels of renewable generation, fundamental changes are required to address real-time situational awareness. This paper uses unique tr…
GRATE: Granular Recovery of Aggregated Tensor Data by Example
Ahmed S. Zamzam, Bo Yang, Nicholas D. Sidiropoulos
In this paper, we address the challenge of recovering an accurate breakdown of aggregated tensor data using disaggregation examples. This problem is motivated by several applicatio…
Power System State Estimation via Feasible Point Pursuit: Algorithms and Cramer-Rao Bound
Gang Wang, Ahmed S. Zamzam, Georgios B. Giannakis +1
Accurately monitoring the system's operating point is central to the reliable and economic operation of an electric power grid. Power system state estimation (PSSE) aims to obtain…