Application of adaptive EEMD method in voltage sag detection

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CIRED 2019 - 483.pdf (573.81 KB)

Paper number

483

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Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

Short title

Convener

Authors

SONG, Jie, State Grid Shanghai EPRI, China
XIAO, Qishi, State Grid Shanghai EPRI, China
PAN, Ling, State Grid Shanghai EPRI, China
JIN, Yongjun, Liandi(Nanjing) Information Systems Co. Ltd., China
MA, Zengyun, Liandi(Nanjing) Information Systems Co. Ltd., China

Abstract

In the traditional Ensemble Empirical Mode Decomposition (EEMD) method, the two critical parameters (the amplitude of the added white noise and the number of ensemble trials) are required to be obtained artificially and the added-noise process is non-adaptive. Aiming at the shortcomings of EEMD method, a modified Ensemble Empirical Mode Decomposition (MEEMD) method was proposed. In the proposed method, the added-noise principle of noise assisted decomposition methods were analyzed, and the two parameters: signal-to-noise ratio and correlation coefficient were taken as an evaluation index of decomposition performance, which adaptively determined the optimal amplitude of additive white-noise and number of ensemble trials by calculating the SNR values under different noises and the correlation between obtained components and original components. Furthermore, simulation results show that the proposed method is able to effectively suppress mode mixing and endpoint effects. At last, experiments data measured from the built power quality disturbance platform demonstrate that the proposed method is capable to accurately extract all disturbance parameters of voltage sag, which provides a novel way for power quality disturbance analysis as well.

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Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/33
http://dx.doi.org/10.34890/67

ISSN

2032-9644

ISBN

978-2-9602415-0-1