A Classification Method of Power Quality Mixed Disturbances Based on Time-Frequency Domain Multi-Feature Quantities

A power quality disturbance and multi-feature quantity technology, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve problems such as mutual influence and complex signal characteristics, and achieve the effect of solving interference

CN102831433BInactive Publication Date: 2016-11-30SOUTHWEST JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Publication Date
2016-11-30
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a method for classifying power quality mixed disturbances based on time-frequency domain multi-feature quantities. Classify voltage sags, voltage swells, voltage short-time interruptions, pulse transients, oscillation transients, harmonics and flicker power quality disturbances and their combined disturbances. The specific implementation steps first use clustering The empirical model decomposition method EEMD and the improved incomplete S-transform MIST process the disturbance signal, and extract 9 time-frequency domain feature values; then, the feature quantities are input into the block-based automatic classification system for disturbance identification. This method fully considers the mutual interference between single disturbances, and effectively suppresses them through complementary time-frequency domain feature quantities. The simulation results show that under certain noise conditions, the method can effectively classify power quality disturbances such as voltage sags, voltage swells, voltage short interruptions, pulse transients, oscillation transients, harmonics and flicker and their combinations. into a mixed disturbance.
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Description

technical field

[0001] The invention relates to a new method for classifying electric energy quality mixed disturbances based on time-frequency domain multi-feature quantities. Background technique

[0002] In recent years, power quality issues have received widespread attention from all walks of life. In-depth study of various factors affecting power quality, accurate extraction of power quality disturbance signal characteristics, and correct classification of power quality disturbances are the premise and basis for power quality analysis and evaluation.

[0003] So far, a large number of scholars at home and abroad have studied the classification of power quality and achieved certain results. However, in actual power systems, power quality disturbances are often mixed disturbances, and multiple disturbances may exist at the same time. Most of the existing power quality disturbance classification methods are for the classification of single disturbances, and it is difficu...

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Embodiment Construction

[0088] Embodiment of the present invention is described in detail below in conjunction with accompanying drawing: present embodiment implements under the premise of technical scheme of the present invention, has provided detailed implementation process, but protection scope of the present invention is not limited to following embodiment.

[0089] figure 1 It is the overall algorithm flow chart of the present invention.

[0090] A. Generation of original data of power quality mixed disturbance

[0091] Since the actual sampling signal cannot fully reflect the diversity of disturbance signals, MATLAB software is used to randomly generate normal signals, sags, swells, short-time interruptions, pulse transients, oscillation transients, harmonics and flicker. Single disturbances and 40 mixed disturbances.

[0092] Each type randomly generates 50 samples, the signal fundamental frequency is 50Hz, and the signal sampling frequency is 3.2kHz. All signals are superimposed with Gaus...