A simple method to detect internal and external short-circuit faults, classify and locate different internal faults in t
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ORIGINAL PAPER
A simple method to detect internal and external short-circuit faults, classify and locate different internal faults in transformers Hossein Ahmadi1 · Behrooz Vahidi1
· Amin Foroughi Nematollahi1
Received: 11 March 2020 / Accepted: 6 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract In new power systems, transformer monitoring and on-time detection of internal faults in power transformers are of great importance because if these faults are not identified on-time, the lifetime of the transformer might be reduced, the transformer might be completely disconnected, and network reliability might decrease. In this paper, a new method is proposed to detect internal and external short-circuit faults. It also allows us to classify and locate different internal short-circuit faults offline in power transformers. The proposed method is based on creating a locus curve of voltage–current difference (V − I ) for all three phases of the transformer. This method can be implemented simply without requiring special equipment and only through monitoring terminal quantities of the transformer. In order to investigate the behavior of transformers in the presence of internal short-circuit fault, the finite element method is used. By investigating variations of locus diagrams concerning to the normal state, fault type and fault location are determined. The proposed method is applied to a distribution transformer white Yzn5 connection successfully. Simulation results verify the capability of the proposed method in transformer monitoring. Keywords Power transformer monitoring · Finite element method (FEM) · Internal and external short-circuit faults
1 Introduction Transformers are integral parts of power systems that establish a vital link between generation and consumption. Thus, avoiding faults in power transformers, especially faults that result in transformer failure are significant for network utilizers. Today, online transformer monitoring has attracted attentions due to fast awareness of fault occurrence, preventing complete disconnection of the transformer, reliability improvement and providing better services to the customers [1, 2]. Faults which may occur in a power transformer include internal and external faults [3]. Among faults which fail the transformer, winding faults, which are mainly internal faults, play a more prominent role [1, 2, 4]. The internal winding faults such as turn-to-turn, phase-to-phase, and phase-toground fault cannot be detected easily, if the intensity of the fault is small. For instance, for an internal turn-to-turn fault, according to IEEE standard C37.91-2000 on power
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Behrooz Vahidi [email protected] Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
transformers, if the number of shorted turns is less than 10% of total turns of the transformer, it will not affect terminal current profoundly. In other words, it can be concluded that protecting transformers against internal winding faults is a challenging tas
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