Multi scale recurrence quantification analysis for clustering harmonics on microgrid systems

In this paper, a Multi Scale Recurrence Quantification Analysis (MSRQA) method is proposed to clustering harmonics on microgrid systems. MSRQA is composed by the Variational Mode Decomposition algorithm and the Recurrence Quantification Analysis (RQA). MSRQA decomposes a signal into a finite number of Mono-Component Signals (MCSs), then a feature extraction is carry out by the RQA on each MCS. Finally, the identification of the optimal number of clusters based on the features extracted by RQA and the Davies-Bouldin index is carry out on the monitored microgrid system test signals. At the end an index based on the cluster information and the RQA measure is proposed to identify the harmonics present on the dynamic system behavior. © 2017 IEEE.

Clustering Harmonic Analysis; Feature Extraction; Microgrid; Multi Scale Recurrence Quantification Analysis (MRQA); Variational Mode Decomposition (VMD) Extraction; Feature extraction; Harmonic analysis; Multivariable control systems; Davies-Bouldin index; Micro grid; Micro-grid systems; Mode decomposition; Mono-component signal; Optimal number; Recurrence quantification analysis; System behaviors; Signal processing

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