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Integration of Accelerated Deep Neural Network Into Power Transformer Differential Protection | IEEE Journals & Magazine | IEEE Xplore

Integration of Accelerated Deep Neural Network Into Power Transformer Differential Protection


Abstract:

Differential protection scheme is the main protection scheme of power transformers, which still holds the risk of sending false trips subject to inrush currents. This art...Show More

Abstract:

Differential protection scheme is the main protection scheme of power transformers, which still holds the risk of sending false trips subject to inrush currents. This article aims to develop a differential protection scheme to discriminate power transformer magnetizing current from internal faults to decrease the risk of false trips. In this article, an accelerated convolutional neural network (CNN) based approach is designed for the discrimination between internal faults and inrush current. The main competitive advantage of the proposed algorithm is its capability in fusing the feature extraction and fault detection blocks into a single deep neural network block by enabling the network to discover important features automatically. The result of this point is that the algorithm is more efficient in terms of speed, hardware usage, and accuracy. The proposed method is applied to a simulated 230-kV network and an experimental prototype. Different cases with various external factors are simulated to calculate reliability indexes. The comparison between the accelerated CNN, conventional CNN, and nine widely used methods demonstrates the faster and more reliable performance of the proposed algorithm.
Published in: IEEE Transactions on Industrial Informatics ( Volume: 16, Issue: 2, February 2020)
Page(s): 865 - 876
Date of Publication: 18 July 2019

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I. Introduction

Power transformers are significantly important devices in power system operation and stability. Thus, it is crucial to protect power transformers against the damages because of the significant role and high cost of transformers. Failures of power transformers are becoming increasingly important, while the power transformer market is projected to reach from 20.71 billion in 2015 to 29.91 billion by 2020 [1]. According to a International Council on Large Electric Systems (CIGRE) technical report, about 11.62% of the power transformers failures are concerned with winding faults [2]. The differential relay is the major protection equipment in large power transformer, owing to its simplicity and fast operation [3]. When a transformer is first energized or experiences a sudden change, a transient current with about eight to ten times larger magnitude than that of the full load current can flow in the transformer windings, which is called inrush current [4]. The differential relay is not always able to distinguish the inrush current from internal faults [3], [5].

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