Detection of Power Quality Disturbances Based on Residual Analysis Using Kalman Filter Based on Maximum Likelihood-Reference-Cited by-同舟云学术

Detection of Power Quality Disturbances Based on Residual Analysis Using Kalman Filter Based on Maximum Likelihood

Published:2019-06-15 Issue:9-10 Volume:47 Page:861-875
ISSN:1532-5008
Container-title:Electric Power Components and Systems
language:en
Short-container-title:Electric Power Components and Systems

Author:

Xi Yanhui¹,Tang Xin¹,Li Zewen¹,Cui Yonglin¹,Zeng Xiangjun¹

Affiliation:

1. Hunan Province Higher Education Key Laboratory of Power System Safety Operation and Control, Changsha University of Science and Technology, Changsha, Hunan Province, China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Energy Engineering and Power Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/15325008.2019.1627607

Reference34 articles.

1. Adaptive threshold based on wavelet transform applied to the segmentation of single and combined power quality disturbances

2. Integrated DWT–FFT approach for detection and classification of power quality disturbances

3. A novel wavelet transform based voltage sag/swell detection algorithm

4. Comparison between discrete STFT and wavelets for the analysis of power quality events

5. HHT-based classification of composite power quality events

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