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In this study, the problem of fault zone detection of distance relaying in FACTS-based transmission lines is analyzed. Existence of FACTS devices on the transmission line, when they are included in the fault zone, from the distance relay point of view, causes different problems in determining the exact location of the fault by changing the impedance seen by the relay. The extent of these changes depends on the parameters that have been set in FACTS devices. To solve the problem associated with these compensators, two instruments for separation and analysis of three-line currents, from the relay point of view at fault instance, have been utilized. The wavelet transform was used to separate the high-frequency components of the three-line currents, and the support vector machine (using methods for multi-class usage) was used for classification of fault location into three protection regions of distance relay. Besides, to investigate the effects of TCSC location on fault zone detection of distance relay, two places, one in fifty percent of line length and the other in seventy-five percent of line length, have been considered as two scenarios for confirmation of the proposed method. Simulations indicate that this method is effective in the protection of FACTS-based transmission lines.
For enhancing transmission performance, privacy level and energy manipulating efficiency of wireless networks, this paper initiates a novel simultaneous wireless information and power transfer (SWIPT) full-duplex (FD) relaying protocol, termed harves
The cost of wind energy can be reduced by using SCADA data to detect faults in wind turbine components. Normal behavior models are one of the main fault detection approaches, but there is a lack of consensus in how different input features affect the
Textual descriptions of the physical world implicitly mention commonsense facts, while the commonsense knowledge bases explicitly represent such facts as triples. Compared to dramatically increased text data, the coverage of existing knowledge bases
This paper presents a novel mutual information (MI) matrix based method for fault detection. Given a $m$-dimensional fault process, the MI matrix is a $m times m$ matrix in which the $(i,j)$-th entry measures the MI values between the $i$-th dimensio
This letter presents a novel high impedance fault (HIF) detection approach using a convolutional neural network (CNN). Compared to traditional artificial neural networks, a CNN offers translation invariance and it can accurately detect HIFs in spite