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Modeling the AC power flow equations with optimally compact neural networks: Application to unit commitment

Journal Article · · Electric Power Systems Research

Not Available

Sponsoring Organization:
USDOE
Grant/Contract Number:
AC02-06CH11357
OSTI ID:
1961698
Alternate ID(s):
OSTI ID: 2377771
Journal Information:
Electric Power Systems Research, Journal Name: Electric Power Systems Research Journal Issue: C Vol. 213; ISSN 0378-7796
Publisher:
ElsevierCopyright Statement
Country of Publication:
Switzerland
Language:
English

References (21)

ReLU networks as surrogate models in mixed-integer linear programs journal December 2019
Neural networks for power flow: Graph neural solver journal December 2020
Network-constrained unit commitment with piecewise linear AC power flow constraints journal June 2021
The Integration of Explicit MPC and ReLU based Neural Networks journal January 2020
Strong NP-hardness of AC power flows feasibility journal November 2019
Fast power system analysis via implicit linearization of the power flow manifold
  • Bolognani, Saverio; Dorfler, Florian
  • 2015 53rd Annual Allerton Conference on Communication, Control and Computing (Allerton), 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton) https://doi.org/10.1109/ALLERTON.2015.7447032
conference September 2015
Sequential Relaxation of Unit Commitment with AC Transmission Constraints conference December 2018
Graph Neural Solver for Power Systems conference July 2019
Model Compression and Acceleration for Deep Neural Networks: The Principles, Progress, and Challenges journal January 2018
Learning Optimal Power Flow: Worst-Case Guarantees for Neural Networks conference November 2020
Tight and Compact MILP Formulation of Start-Up and Shut-Down Ramping in Unit Commitment journal May 2013
The Unit Commitment Problem With AC Optimal Power Flow Constraints journal November 2016
Global Solution Strategies for the Network-Constrained Unit Commitment Problem With AC Transmission Constraints journal March 2019
Efficient Bound Tightening Techniques for Convex Relaxations of AC Optimal Power Flow journal September 2019
Approximating Trajectory Constraints With Machine Learning – Microgrid Islanding With Frequency Constraints journal March 2021
Physics-Guided Deep Neural Networks for Power Flow Analysis journal May 2021
Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning With Region-of-Interest Active Sampling journal May 2022
Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications journal January 2021
Solutions of DC OPF are Never AC Feasible conference June 2021
PowerModels. JL: An Open-Source Framework for Exploring Power Flow Formulations conference June 2018
Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming conference August 2017

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