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Encoding Frequency Constraints in Preventive Unit Commitment Using Deep
Learning with Region-of-Interest Active Sampling

v1v2 (latest)

Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning with Region-of-Interest Active Sampling

IEEE Transactions on Power Systems (IEEE Trans. Power Syst.), 2021

18 February 2021

ArXiv (abs)PDF HTML

Papers citing "Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning with Region-of-Interest Active Sampling"

3 / 3 papers shown

Closing the Loop: A Framework for Trustworthy Machine Learning in Power
Systems

Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems

Samuel C. Chevalier

Rahul Nellikkath

Brynjar Sævarsson

Spyros Chatzivasileiadis

302

19

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 CommitmentElectric power systems research (EPSR), 2021

Alyssa Kody

Samuel C. Chevalier

Spyros Chatzivasileiadis

Daniel Molzahn

307

44

0

21 Oct 2021

Exploration of Artificial Intelligence-oriented Power System Dynamic
Simulators

Exploration of Artificial Intelligence-oriented Power System Dynamic Simulators

190

21

0

03 Oct 2021

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