Journal ArticleDOI
Power quality recognition in distribution system with solar energy penetration using S-transform and Fuzzy C-means clustering
TLDR
In this paper, the authors presented a technique to recognize the power quality disturbances associated with solar energy penetration in distribution network using a standard IEEE-13 bus test system modified by incorporating the solar PV system.About:
This article is published in Renewable Energy.The article was published on 2017-06-01. It has received 83 citations till now. The article focuses on the topics: Photovoltaic system & Solar energy.read more
Citations
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Journal ArticleDOI
A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making
TL;DR: The novelty of this work is in the incorporation of an IDM technique FCM-GRP into CHPEED to automatically determine the BCSs that represent decision makers' different, even conflicting, preferences.
Journal ArticleDOI
Comprehensive Review on Detection and Classification of Power Quality Disturbances in Utility Grid With Renewable Energy Penetration
Gajendra Singh Chawda,Abdul Gafoor Shaik,Mahmood Shaik,Sanjeevikumar Padmanaban,Jens Bo Holm-Nielsen,Om Prakash Mahela,Palanisamy Kaliannan +6 more
TL;DR: A critical review of techniques used for detection and classification PQ disturbances in the utility grid with renewable energy penetration is presented, to provide various concepts utilized for extraction of the features to detect and classify the P Q disturbances even in the noisy environment.
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Power Quality Assessment and Event Detection in Distribution Network With Wind Energy Penetration Using Stockwell Transform and Fuzzy Clustering
TL;DR: A novel method for assessing PQ associated with wind energy integration is proposed that is effective to recognize PQ issues in power systems with high penetration of wind energy with a low computational burden and detects different operational issues in the distribution network.
Journal ArticleDOI
Power quality assessment and event detection in hybrid power system
TL;DR: A method based on Stockwell's transform (S-transform) is presented in this paper for power quality (PQ) assessment and detection of islanding, outage and grid synchronization of renewable energy sources.
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Recognition of power quality disturbances using S-transform based ruled decision tree and fuzzy C-means clustering classifiers
TL;DR: A method based on Stockwell's transform and Fuzzy C-means clustering initialized by decision tree has been proposed for detection and classification of power quality (PQ) disturbances and is established effectively by results of high accuracy.
References
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Journal ArticleDOI
Detection and classification of power quality disturbances using discrete wavelet transform and wavelet networks
TL;DR: In this article, a novel approach for detection and classification of power quality (PQ) disturbances is proposed, where distorted waveforms are generated based on the IEEE 1159 standard, captured with a sampling rate of 20 kHz and de-noised using discrete wavelet transform (DWT) to obtain signals with higher signal-to-noise ratio.
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Recognition of Power-Quality Disturbances Using S-Transform-Based ANN Classifier and Rule-Based Decision Tree
TL;DR: In this article, an algorithm based on Stockwell's transform and artificial neural network-based classifier and a rule-based decision tree is proposed for the recognition of single stage and multiple power quality (PQ) disturbances.
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Islanding and Power Quality Disturbance Detection in Grid-Connected Hybrid Power System Using Wavelet and $S$ -Transform
TL;DR: Comparison study between wavelet transform (WT) and S-transform (ST) based on extracted features for detection of islanding and power quality (PQ) disturbances in hybrid distributed generation (DG) system demonstrates the advantages of S -transform over WT in detection of Islanding and different disturbances under noise-free as well as noisy scenarios.
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S-transform-based intelligent system for classification of power quality disturbance signals
I.W.C. Lee,Pradipta Kishore Dash +1 more
TL;DR: A new approach is presented for the detection and classification of nonstationary signals in power networks by combining the S-transform and neural networks and is found to be a significant improvement over multiresolution wavelet analysis with multiple neural networks.
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An expert system based on S-transform and neural network for automatic classification of power quality disturbances
TL;DR: The S-transform (ST) technique is integrated with neural network (NN) model with multi-layer perceptron to construct the classifier that can effectively classify different PQ disturbances.