Online Prediction and Correction of Static Voltage Stability Index Based on Extreme Gradient Boosting Algorithm

With the increasing integration of renewable energy sources into the power grid and the continuous expansion of grid infrastructure, real-time preventive control becomes crucial. This article proposes a real-time prediction and correction method based on the extreme gradient boosting (XGBoost) algor...

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Vydáno v:	Energies (Basel) Ročník 17; číslo 22; s. 5710
Hlavní autoři:	Qin, Huiling, Li, Shuang, Zhang, Juncheng, Rao, Zhi, He, Chengyu, Chen, Zhijun, Li, Bo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Basel MDPI AG 01.11.2024
Témata:	Accuracy Algorithms Alternative energy sources Analysis Decision trees Electricity distribution Energy consumption extreme gradient boosting (XGBoost) algorithm Feature selection Genetic algorithms Infrastructure (Economics) Machine learning Methods Neural networks preventive control real-time prediction sensitivity approximation static voltage stability Support vector machines Wind power
ISSN:	1996-1073, 1996-1073
On-line přístup:	Získat plný text
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