Proceedings ArticleDOI
Experimental investigation of power quality disturbances associated with grid integrated wind energy system
TLDR
It has been observed that the PQ disturbances such as voltage fluctuations, flicker, voltage sag, voltage swell and harmonics are associated with the grid synchronization and outage of DFIG based wind energy conversion system.Abstract:
This paper presents the experimental investigation of power quality (PQ) disturbances associated with the grid integrated wind energy generator. PQ disturbances associated with the grid synchronization and outage of doubly fed induction generator (DFIG) based wind energy generation system have been investigated in the presence of various types of loads. The voltage signal has been captured at point of common coupling (PCC) using the data acquisition system consisting of power quality analyser, laptop, and WT viewer software. The voltage signal has been analysed using MATLAB software to find the PQ disturbances. It has been observed that the PQ disturbances such as voltage fluctuations, flicker, voltage sag, voltage swell and harmonics are associated with the grid synchronization and outage of DFIG based wind energy conversion system.read more
Citations
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Journal ArticleDOI
A review of power quality compatibility of wind energy conversion systems with the South African utility grid
TL;DR: Now that grid connected large scale wind farms are in operation, an opportunity exists to install power quality recorders and use actual field measurements to gain an understanding of the compatibility of WECS with the South African utility grid.
Proceedings ArticleDOI
Events Recognition and Power Quality Estimation in Distribution Network in the Presence of Solar PV Generation
TL;DR: In this article, a method using features computed from voltage by applying Hilbert transform (HT) and Stockwell transform (ST) for event recognition and power quality (PQ) estimation in distribution network (DN) interfaced to the solar photovoltaic (PV) generation is presented.
Proceedings ArticleDOI
Indirect Vector Control of DFIG Based Wind Energy System Using Fuzzy-PI Controller
TL;DR: The implementation of indirect vector control technique to control the speed of a doubly fed induction generator using Fuzzy logic as a control algorithm instead of traditional control technique for the fine tune of controller.
References
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Journal ArticleDOI
A critical review of detection and classification of power quality events
TL;DR: A comprehensive review of signal processing and intelligent techniques for automatic classification of the power quality (PQ) events and an effect of noise on detection and classification of disturbances is presented in this paper.
Journal ArticleDOI
An effective wavelet-based feature extraction method for classification of power quality disturbance signals
TL;DR: A wavelet norm entropy-based effective feature extraction method for power quality (PQ) disturbance classification problem and a classification algorithm composed of a wavelet feature extractor based on norm entropy and a classifier based on a multi-layer perceptron are presented.
Journal ArticleDOI
Detection and Classification of Power Quality Disturbances Using Sparse Signal Decomposition on Hybrid Dictionaries
TL;DR: A new method for detection and classification of single and combined PQ disturbances using a sparse signal decomposition (SSD) on overcomplete hybrid dictionary (OHD) matrix that can be easily expanded for compressed sensing based PQ monitoring networks.
Journal ArticleDOI
A Classification Method for Complex Power Quality Disturbances Using EEMD and Rank Wavelet SVM
Zhigang Liu,Yan Cui,Wenhui Li +2 more
TL;DR: Simulation results and real-time digital simulator tests show that the rank-WSVM classification performance of complex disturbances including hamming loss, ranking loss, one-error, coverage, and average precision, is generally better than the other three methods, namely rank-SVM, multilabel naive Bayes, andMultilabel learning with backpropagation.
Journal ArticleDOI
Detection and Classification of Multiple Power-Quality Disturbances With Wavelet Multiclass SVM
TL;DR: An integrated model for recognizing power-quality disturbances (PQD) using a novel wavelet multiclass support vector machine (WMSVM) which is capable of processing multiple classification problems.