AUTHOR=Wei Yang , Li Chen , Ai Yuangao , Shen Hongwan , Zeng Shai , Sun Yue TITLE=Analysis of primary side turn-to-turn short circuit fault in PT at the generator outlet and diagnosis using CSSA-GMM JOURNAL=Frontiers in Energy Research VOLUME=Volume 12 - 2024 YEAR=2024 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2024.1504706 DOI=10.3389/fenrg.2024.1504706 ISSN=2296-598X ABSTRACT=

In power systems, potential transformers (PTs) are responsible for stepping down high voltage to low voltage. However, a short circuit between turns on the primary side of a generator outlet PT can significantly reduce the secondary phase voltage, leading to voltage imbalances and generating fundamental zero-sequence voltage. This situation is analogous to a stator winding ground fault, often resulting in incorrect protective operations. To prevent such malfunctions, this paper analyzes the causes of false tripping through simulation and proposes a fault diagnosis model based on the Circular Sparrow Search Algorithm (CSSA)-optimized Gaussian Mixture Model (GMM), referred to as the CSSA-GMM model. A fault simulation model was established using Simulink to verify the differences between turn-to-turn short circuits and stator ground faults, and their electrical characteristics were studied. The results indicate that under different fault types, parameters such as the three-phase primary current and three-phase secondary voltage exhibit varying relationships and fault variations. By optimizing the GMM parameters using CSSA and comprehensively analyzing the voltage and current characteristics, this model can effectively diagnose turn-to-turn short circuit faults at various short-turn ratios, achieving an accuracy rate of up to 98%. This approach clearly distinguishes PT turn-to-turn short circuits from generator outlet stator ground faults, providing new insights for fault recognition and supporting the intelligent development of relay protection systems.