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04/23/2023
End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch
The paper proposes a novel End-to-End Learning and Repair (E2ELR) archit...
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11/28/2022
Confidence-Aware Graph Neural Networks for Learning Reliability Assessment Commitments
Reliability Assessment Commitment (RAC) Optimization is increasingly imp...
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09/26/2022
Just-In-Time Learning for Operational Risk Assessment in Power Grids
In a grid with a significant share of renewable generation, operators wi...
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08/16/2022
Active Bucketized Learning for ACOPF Optimization Proxies
This paper considers optimization proxies for Optimal Power Flow (OPF), ...
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05/08/2022
Learning Regionally Decentralized AC Optimal Power Flows with ADMM
One potential future for the next generation of smart grids is the use o...
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04/02/2022
Risk-Aware Control and Optimization for High-Renewable Power Grids
The transition of the electrical power grid from fossil fuels to renewab...
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12/27/2021
Learning Optimization Proxies for Large-Scale Security-Constrained Economic Dispatch
The Security-Constrained Economic Dispatch (SCED) is a fundamental optim...
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10/26/2021
Data-Driven Time Series Reconstruction for Modern Power Systems Research
A critical aspect of power systems research is the availability of suita...
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10/16/2019
