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Found 7 papers, 0 papers with code
Toward Rapid, Optimal, and Feasible Power Dispatch through Generalized Neural Mapping
The evolution towards a more distributed and interconnected grid necessitates large-scale decision-making within strict temporal constraints.
Machine Learning Infused Distributed Optimization for Coordinating Virtual Power Plant Assets
Amid the increasing interest in the deployment of Distributed Energy Resources (DERs), the Virtual Power Plant (VPP) has emerged as a pivotal tool for aggregating diverse DERs and facilitating their participation in wholesale energy markets.
Learning to Solve Optimization Problems with Hard Linear Constraints
We demonstrate the performance of our proposed method in quadratic programming in the context of the optimal power dispatch (critical to the resiliency of our electric grid) and a constrained non-convex optimization in the context of image registration problems.
Numerical Comparisons of Linear Power Flow Approximations: Optimality, Feasibility, and Computation Time
Linear approximations of the AC power flow equations are of great significance for the computational efficiency of large-scale optimal power flow (OPF) problems.
A Fully Decentralized Tuning-free Inexact Projection Method for P2P Energy Trading
Agent-based solutions lend themselves well to address privacy concerns and the computational scalability needs of future distributed electric grids and end-use energy exchanges.
Teaching Networks to Solve Optimization Problems
In addition, we propose two alternative approaches for learning such parametric functions, with and without a solver in the LOOP.
Virtual Inertia Control of the Virtual Synchronous Generator: A Review
With the increasing impact of low inertia due to the high penetration of distributed generation, virtual synchronous generator (VSG) technology has been proposed to improve the stability of the inverter-interfaced distributed generator by providing "virtual inertia".
