Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data

Transition towards carbon-neutral power systems has necessitated optimization of power dispatch in active distribution networks (ADNs) to facilitate integration of distributed renewable generation. Due to unavailability of network topology and line impedance in many distribution networks, physical m...

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Bibliographic Details
Main Authors: Yonghua Song, Ge Chen, Hongcai Zhang
Format: Article
Language:English
Published: China electric power research institute 2024-01-01
Series:CSEE Journal of Power and Energy Systems
Subjects:
Deep learning
demand response
distribution networks
imbalanced data
optimal power flow
Online Access:https://ieeexplore.ieee.org/document/10375977/
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