Modeling the AC Power Flow Equations with Optimally Compact Neural
Networks: Application to Unit Commitment

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

21 October 2021

Alyssa Kody

Samuel C. Chevalier

Spyros Chatzivasileiadis

Daniel Molzahn

Papers citing "Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment"

10 / 10 papers shown

Title
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 117 36 0 29 Apr 2023
Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning with Region-of-Interest Active Sampling Yichen Zhang Hantao Cui Jianzhe Liu F. Qiu Tianqi Hong Rui Yao F. Li 26 62 0 18 Feb 2021
A Survey on Deep Neural Network Compression: Challenges, Overview, and Solutions Rahul Mishra Hari Prabhat Gupta Tanima Dutta 28 90 0 05 Oct 2020
Learning Optimal Power Flow: Worst-Case Guarantees for Neural Networks Andreas Venzke Guannan Qu S. Low Spyros Chatzivasileiadis 13 65 0 19 Jun 2020
Neural Networks for Encoding Dynamic Security-Constrained Optimal Power Flow Daniel Timon Viola Andreas Venzke George S. Misyris Spyros Chatzivasileiadis 99 38 0 17 Mar 2020
Contextual Reserve Price Optimization in Auctions via Mixed-Integer Programming Joey Huchette Haihao Lu Hossein Esfandiari Vahab Mirrokni 50 7 0 20 Feb 2020
Physics-Guided Deep Neural Networks for Power Flow Analysis Xinyue Hu Haoji Hu Saurabh Verma Zhi-Li Zhang 175 125 0 31 Jan 2020
Approximating Trajectory Constraints with Machine Learning -- Microgrid Islanding with Frequency Constraints Yichen Zhang Chen Chen Guodong Liu Tianqi Hong F. Qiu 33 40 0 16 Jan 2020
Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications Andreas Venzke Spyros Chatzivasileiadis 33 67 0 03 Oct 2019
ReLU Networks as Surrogate Models in Mixed-Integer Linear Programs B. Grimstad H. Andersson 46 140 0 06 Jul 2019