Data-Driven Proactive Early Warning of Grid Congestion Probability Based on Multiple Time Scales

Data-Driven Proactive Early Warning of Grid Congestion Probability Based on Multiple Time Scales

With the development of new power systems, the increased interactive demand on the load side, and the high proportion of renewable energy sources on the power side, grid congestion problems due to increased system uncertainty are becoming more frequent. In this context, grid congestion problems have...

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Bibliographic Details
Main Authors: Haobo Fu, Ruizhuo Wang, Bingxu Zhai, Yuanzhuo Li, Pengyuan Li, Rui Zhang, Haoyuan He, Siyang Liao
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Energies
Subjects:
data-driven
feature selection
machine learning
probabilistic prediction
grid congestion warning
active regulation
Online Access:https://www.mdpi.com/1996-1073/18/10/2530
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