Single phase and three phase power quality disturbance Recognition using S-transform
Publish place: 25th International Power System Conference
Publish Year: 1389
نوع سند: مقاله کنفرانسی
زبان: English
View: 1,647
This Paper With 10 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
PSC25_027
تاریخ نمایه سازی: 24 بهمن 1390
Abstract:
in this paper s-transform is introduced as an effective method for power quality disturbance recognition. S-transform is a time-frequency analyzing technique that bridges the gap between the short-time Fourier transform and wavelet transform. The features obtained from ST are distinct, understandable and immune to noise. In proposed method by use of s-transform and a decision making algorithm, thirteen kinds of single disturbances like sag, swell, interrupt, harmonic, spike, notch, noise, oscillatory transient, flicker, sub-harmonic, DC, interharmonic, unbalancy, and two complex disturbances are well recognized. The waves extracted from s-transform let us to investigate PQ disturbances in three phases simultaneously. Therefore disturbances like unbalancy and different sag types can be well recognized. After extracting three features from disturbance signals by means of Stransform, ten distinct indices for each signal will be extracted. By means of these indices and a rule-based decision tree various types of power quality disturbances can be classified. For simulation purpose disturbances with random parameters has been produced and for better similarity to real signals they are mixed with noises with different SNR values. It shows that this method can be used for real applications.
Keywords:
Authors
S Hasheminejad
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
s esmaeili
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
A.A .gharaveisi
Department of Electrical Engineering, Shahid Bahonar University of Kerman, Kerman, Iran
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :