Fault detection in the secondary side of electric arc furnace transformer using the primary side data

SUMMARY This paper presents a novel methodology for detecting fault conditions in the secondary side of electric arc furnace (EAF) transformer. The major focus of this study is to design a digital algorithm which uses solely the primary side current. Therefore, in this new methodology, only the primary side current is measured, and the fault presence in the secondary side is investigated. Here, there are two main objectives. The first objective is minimizing the fail-to-trip functioning probability, and the second one is minimizing the Mal-Trip operation probability. The fault characteristics are extracted using accurate simulation of EAFs installed in the Mobarakeh Steel Company (MSC) in Isfahan, Iran to fulfill the first objective. Three-phase field data of instantaneous current from the primary side of eight EAF transformers of MSC is also provided to evaluate performance of the proposed algorithm in the normal conditions and to achieve the second objective. The proposed algorithm is based on the sudden reduction of current harmonics in the fault conditions which is evaluated by a proposed special index which is called “the difference function” in this paper. Overall reliability assessment (dependability and security) of the proposed protective scheme demonstrates that even in this highly varying and unpredictable environment, the proposed algorithm is so precise and fast in fault detection. Copyright © 2013 John Wiley & Sons, Ltd.

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