EEMD-based power quality disturbance detection method

TaiQing Tang; Ning Zhang; Cong Tian; XiWen Wei

doi:10.1117/12.3004430

25 September 2023 EEMD-based power quality disturbance detection method

TaiQing Tang, Ning Zhang, Cong Tian, XiWen Wei

Proceedings Volume 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023); 127884F (2023) https://doi.org/10.1117/12.3004430
Event: Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 2023, Kuala Lumpur, Malaysia

Abstract

In view of the fact that at the present stage power quality monitoring systems can only detect and identify a single power quality problem, while multiple disturbances may be superimposed on the actual power quality problem, a new monitoring system for the identification of superimposed disturbances in power quality is proposed and its functions are implemented using the LabVIEW platform. The method is to achieve the decomposition and identification of multiple power quality problems using a clustering empirical modal decomposition method. The simulation results show that the optimisation algorithm proposed in this paper can achieve the monitoring of multiple disturbance signals of power quality with good real-time performance and monitoring accuracy. It provides scientific and accurate data support for the improvement of power quality problems, and has good application prospects.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

TaiQing Tang, Ning Zhang, Cong Tian, and XiWen Wei "EEMD-based power quality disturbance detection method", Proc. SPIE 12788, Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023), 127884F (25 September 2023); https://doi.org/10.1117/12.3004430

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