2017 IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS) 2017
DOI: 10.1109/itcosp.2017.8303073
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Cited by 14 publications
(5 citation statements)
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“…When the grid and one or more DG(s) supply power in synchronism to end-users, the DG is in nonislanded (grid-connected) mode, while when the DG is disengaged from the grid and still actively supplying consumers, the DG is in islanded mode [16].Islanding (unintentional islanding) is a significant problem that power engineers are faced with. Islanding can severely impact power quality and can lead to an unsafe working environment [17]. Islanding also hurts protection device coordination.…”
Section: Theoretical Background/ Reviewmentioning
confidence: 99%
“…When the grid and one or more DG(s) supply power in synchronism to end-users, the DG is in nonislanded (grid-connected) mode, while when the DG is disengaged from the grid and still actively supplying consumers, the DG is in islanded mode [16].Islanding (unintentional islanding) is a significant problem that power engineers are faced with. Islanding can severely impact power quality and can lead to an unsafe working environment [17]. Islanding also hurts protection device coordination.…”
Section: Theoretical Background/ Reviewmentioning
confidence: 99%
“…Since the hallmark of the CNN is image classification, the 2 dimensional version of the discrete convolution is used. To serve as a reminder, the 2 dimensional discrete convolution operation is shown in Equation (6). The convolutional layer works by adjusting the parameter ω for each backpropagation in order to maximize the features extracted by minimizing the error in classification.…”
Section: Convolutional Layermentioning
confidence: 99%
“…To do this, several techniques are currently exploited using machine learning algorithms [3]. Among the extensive inventories of deep learning algorithms, for the present work, the Long Short Term Memory (LSTM) and the Convolutional Neural Networks (CNN) are being used to detect and classify these disturbances [4][5][6]. Other algorithms are being used to address these problems like the Kalman Filter, Wavelet Transform and the Support Vector Machine (SVM).…”
Section: Introductionmentioning
confidence: 99%
“…Statistical feature extractions are usually being carried out after signal analysis stage [15,16]. Statistical features such as mean, median, RMS, standard deviation, variance, and norm, are extracted as the output features before passing into next stage for higher-order feature extraction.…”
Section: Introductionmentioning
confidence: 99%