Polynomial surface-fitting evaluation of new energy maximum power generation capacity based on random forest association analysis and support vector regression

Polynomial surface-fitting evaluation of new energy maximum power generation capacity based on random forest association analysis and support vector regression

Focusing on frequency problems caused by wind power integration in ultra-high-voltage DC systems, an accurate assessment of the maximum generation capacity of large-scale new energy sources can help determine the available frequency regulation capacity of new energy sources and improve the frequency...

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Bibliographic Details
Main Authors:	Yuzhuo Hu, Hui Li, Yuan Zeng, Qichao Chen, Haosen Cao, Wei Chen
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2023-12-01
Series:	Frontiers in Energy Research
Subjects:	random forest feature selection polynomial fitting surfaces whale optimization support vector regression machine
Online Access:	https://www.frontiersin.org/articles/10.3389/fenrg.2023.1323559/full

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