An Adaptive Detection and Clustering Method of Harmonic From Noisy Signal Based on Prony
- Resource Type
- Conference
- Authors
- Jiao, Hao; Wang, Qingpeng; Li, Yuxuan; Shan, Baofeng; Cui, Xinyue; Jin, Zongshuai
- Source
- 2023 8th International Conference on Power and Renewable Energy (ICPRE) Power and Renewable Energy (ICPRE), 2023 8th International Conference on. :804-808 Sep, 2023
- Subject
- Power, Energy and Industry Applications
Performance evaluation
Renewable energy sources
Clustering methods
Simulation
Power system harmonics
Harmonic analysis
Numerical simulation
Harmonic detection
clustering
power system
noisy signal
- Language
- ISSN
- 2768-0525
The increasing penetration of renewable energy resources based on power electronic devices results in increasing levels of harmonic distortion. It is necessary to improve the harmonic monitoring and control ability. The performance of the Prony algorithm can be promised if the order of Prony is set to half of the window length, but this will introduce many pseudo harmonic modes which interfere the harmonic mechanism screening. To solve the problem above, this paper proposes a detection and clustering method of harmonic from noisy signal. The exactly existed harmonics are adaptively detected using the estimated threshold that can reflect the level of pseudo harmonic modes caused by the time-varying background noise. Then, the harmonics of different mechanisms are classified by the agglomerative nesting (AGNES) hierarchical clustering method in the unsupervised sense. The performance of the proposed method has been verified by the numerical simulation.