LES based power quality data feature extraction and Thompson Tau data cleaning

Ke Liu; Laijun Chen; Nanfang Li; Zhiyang Xu; Wenqian Zhang; Xiaoling Su

doi:10.1117/12.2686878

10 August 2023 LES based power quality data feature extraction and Thompson Tau data cleaning

Ke Liu, Laijun Chen, Nanfang Li, Zhiyang Xu, Wenqian Zhang, Xiaoling Su

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 1275910 (2023) https://doi.org/10.1117/12.2686878
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

As power system see increasing application of big data and artificial intelligence, the new generation of power quality data requires cross-platform interaction, larger database support volume, and higher data processing speed, which makes traditional power quality data collection and processing methods difficult to adapt to the power grid development. This paper proposes a power quality Thompson tau algorithm data cleaning strategy based on LES feature extraction, first extract LES feature value of power quality data and cluster partition of the eigenvalues, and then, according to the power quality characteristics of the data partition, divide the sub-interval step flexibly for Thompson tau data cleaning and multipoint interpolation data filling. Finally, power quality data from a practical power grid is taken as an example and the simulation results verify the feasibility and accuracy of the proposed method.

Citation Download Citation

Ke Liu, Laijun Chen, Nanfang Li, Zhiyang Xu, Wenqian Zhang, and Xiaoling Su "LES based power quality data feature extraction and Thompson Tau data cleaning", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 1275910 (10 August 2023); https://doi.org/10.1117/12.2686878

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available