Wavelets as a tool for power system dynamic events analysis – State-of-the-art and future applications
Samir Avdakovic,Nejra Čišija +1 more
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TLDR
In this article, a review of Wavelet Transform (WT) applications for power system dynamic behavior analysis is presented, and it can be concluded that WT technique has different applications in disturbances identification and localization, LFEO identification and analysis, and assessment of active power imbalance.About:
This article is published in Journal of Electrical Systems and Information Technology.The article was published on 2015-05-01 and is currently open access. It has received 14 citations till now. The article focuses on the topics: Electric power system & AC power.read more
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Journal ArticleDOI
Learning Driver Braking Behavior Using Smartphones, Neural Networks and the Sliding Correlation Coefficient: Road Anomaly Case Study
TL;DR: A new method, based on deep neural networks and the sliding correlation coefficient, is proposed for the spatio-temporal correlation of road anomalies and driver behavior and proves to be a robust and flexible tool for self-learning driver behavior.
Proceedings ArticleDOI
Distribution of Wind Power Generation Dependently of Meteorological Factors
Olena Rubanenko,Oleksandr Miroshnyk,Sergiy Shevchenko,Vitalii Yanovych,Dmytro Danylchenko,Oleksandr Rubanenko +5 more
TL;DR: Analyses of trends increasing annual wind power plant capacity and power generation in the World and Europe are presented in this paper, where the main problems of increasing the power generation of renewable energy sources in distributed power grids are investigated and proposed ways to decide them by taking into account the supply of power balance, reliability operating of the power grid, and electric power quality.
Journal ArticleDOI
Review of Signal Processing Techniques and Machine Learning Algorithms for Power Quality Analysis
TL;DR: A comprehensive review of various power quality analysis techniques such as heuristic optimization, signal processing, machine learning, neural networks, artificial intelligence, and hardware implementation is presented so that a brief overview will be presented to the researcher and power engineers working in the field of power quality.
Proceedings ArticleDOI
Detection, characterization and classification of short duration voltage events using DWT and fuzzy logic
TL;DR: In this article, a combination of discrete wavelet transform (DWT) and fuzzy logic has been used to classify short and long duration voltage disturbances in industrial and commercial power supply.
Journal ArticleDOI
A hybrid method for fault location estimation in a fixed series compensated lines
Aleena Swetapadma,Anamika Yadav +1 more
TL;DR: A fault distance estimation scheme for fixed series capacitor compensated parallel transmission lines using discrete wavelet transform and decision tree regression and test result ensures that, it can estimate the fault distance accurately.
References
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Book
A wavelet tour of signal processing
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Book
Ten lectures on wavelets
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Journal ArticleDOI
Ten Lectures on Wavelets
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.
Book
Synchronized Phasor Measurements and Their Applications
Arun G. Phadke,James S. Thorp +1 more
TL;DR: Phasor Measurement Techniques and Applications: Estimation of Nominal Frequency Inputs and Phasor Estimation at Off-Nominal Frequency inputs.
Book
Wavelets: Theory and Applications for Manufacturing
Robert X. Gao,Ruqiang Yan +1 more
TL;DR: In this paper, a wavelet packet decomposition for cross-term interference suppression in wigner-ville distribution has been proposed for discriminable feature extraction, based on wavelet selection criteria.