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Higher-order motif-based time series classification for forced oscillation source location in power grids

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Abstract

Time series motifs are used for discovering higher-order structures of time series data. Based on time series motifs, the motif embedding correlation field (MECF) is proposed to characterize higher-order temporal structures of dynamical system time series. A MECF-based unsupervised learning approach is applied in locating the source of the forced oscillation (FO), a periodic disturbance that detrimentally impacts power grids. Locating the FO source is imperative for system stability. Compared with the Fourier analysis, the MECF-based unsupervised learning is applicable under various FO situations, including the single FO, FO with resonance, and multiple concurrent FOs. The MECF-based unsupervised learning is a data-driven approach without any prior knowledge requirement of system models or typologies. Tests on the UK high-voltage transmission grid are conducted to validate the effectiveness of MECF-based unsupervised learning. In addition, the impacts of coupling strength and measurement noise on locating the FO source by the MECF-based unsupervised learning are investigated. Simulation results show that within typical ranges of coupling strength and measurement noise standard deviation of power systems, the MECF-based unsupervised learning is completely correct in locating the single FO, FO with resonance, and multiple concurrent FOs.

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Acknowledgements

The authors would like to thank the HPC Platform, Xi’an Jiaotong University. Long Huo acknowledges the China Scholarship Council (CSC) scholarship. The pre-print of this article can be found at https://arxiv.org/abs/2306.13397.

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  1. Center of Nanomaterials for Renewable Energy, State Key Laboratory of Electrical Insulation and Power Equipment, School of Electrical Engineering, Xi’an Jiaotong University, Xi’an, 710054, Shaanxi, China

    Long Huo & Xin Chen

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  1. Long Huo
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  2. Xin Chen
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Correspondence to Xin Chen.

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Huo, L., Chen, X. Higher-order motif-based time series classification for forced oscillation source location in power grids. Nonlinear Dyn 111, 20127–20138 (2023). https://doi.org/10.1007/s11071-023-08918-5

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