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Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems
To maintain a reliable grid we need fast decision-making algorithms for complex problems like Dynamic Reconfiguration (DyR).
Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems
Mixed integer problems are ubiquitous in decision making, from discrete device settings and design parameters, unit production, and on/off or yes/no decision in switches, routing, and social networks.
Reinventing the Utility for DERs: A Proposal for a DSO-Centric Retail Electricity Market
The increasing penetration of intermittent renewables, storage devices, and flexible loads is introducing operational challenges in distribution grids.
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