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Approximating Trajectory Constraints with Machine Learning -- Microgrid
  Islanding with Frequency Constraints

Approximating Trajectory Constraints with Machine Learning -- Microgrid Islanding with Frequency Constraints

16 January 2020
Yichen Zhang
Chen Chen
Guodong Liu
Tianqi Hong
F. Qiu
ArXivPDFHTML

Papers citing "Approximating Trajectory Constraints with Machine Learning -- Microgrid Islanding with Frequency Constraints"

4 / 4 papers shown
Title
Massively Digitized Power Grid: Opportunities and Challenges of
  Use-inspired AI
Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI
Le Xie
Xiangtian Zheng
Yannan Sun
Tong Huang
Tony Bruton
AI4CE
35
17
0
10 May 2022
Closing the Loop: A Framework for Trustworthy Machine Learning in Power
  Systems
Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems
Jochen Stiasny
Samuel C. Chevalier
Rahul Nellikkath
Brynjar Sævarsson
Spyros Chatzivasileiadis
29
14
0
14 Mar 2022
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
Alyssa Kody
Samuel C. Chevalier
Spyros Chatzivasileiadis
Daniel Molzahn
66
37
0
21 Oct 2021
Encoding Frequency Constraints in Preventive Unit Commitment Using Deep
  Learning with Region-of-Interest Active Sampling
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
13
62
0
18 Feb 2021
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