Accelerating transmission-constrained unit commitment via a data-driven learning framework

Accelerating transmission-constrained unit commitment via a data-driven learning framework

As a fundamental task in power system operations, transmission-constrained unit commitment (TCUC) decides ON/OFF state (i.e., commitment) and scheduled generation for each unit. Generally, TCUC is formulated as a mixed-integer linear programming (MILP) and must be resolved within a limited time wind...

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Bibliographic Details
Main Authors: Zhaohang Lin, Ying Chen, Jing Yang, Chao Ma, Huimin Liu, Liwei Liu, Li Li, Yingyuan Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-01-01
Series:Frontiers in Energy Research
Subjects:
transmission-constrained unit commitment
machine learning
data-driven
artificial intelligence
power system operation
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2022.1012781/full

Internet

https://www.frontiersin.org/articles/10.3389/fenrg.2022.1012781/full

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