A Data-Driven Approach for Online Inter-Area Oscillatory Stability Assessment of Power Systems Based on Random Bits Forest Considering Feature Redundancy

A Data-Driven Approach for Online Inter-Area Oscillatory Stability Assessment of Power Systems Based on Random Bits Forest Considering Feature Redundancy

To utilize the rapidly refreshed operating data of power systems fully and effectively, an integrated scheme for inter-area oscillatory stability assessment (OSA) is proposed in this paper using a compositive feature selection unit and random bits forest (RBF) algorithm. This scheme consists of offl...

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Bibliographic Details
Main Authors: Songkai Liu, Dan Mao, Tianliang Xue, Fei Tang, Xin Li, Lihuang Liu, Ruoyuan Shi, Siyang Liao, Menglin Zhang
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Energies
Subjects:
inter-area oscillatory stability
feature redundancy
random bits forest
data-driven
Online Access:https://www.mdpi.com/1996-1073/14/6/1641

Internet

https://www.mdpi.com/1996-1073/14/6/1641

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