Detecção de correntes de inrush em transformadores de potência: análise comparativa e uma nova proposta baseada em Transformada Wavelet Sincronizada e Bag of Features
Also known as inrush current, magnetizing current arises during transformer energization. Due to its transient characteristics and high amplitude, this current can cause unwanted operations of protection relays, resulting in incorrect tripping. The main objective of this work is to compare different...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | Brasil |
| Institución: | Universidade Federal do Pampa (UNIPAMPA) |
| Repositorio: | Repositório Institucional da UNIPAMPA |
| Idioma: | portugués |
| OAI Identifier: | oai:repositorio.unipampa.edu.br:123456789/10514 |
| Acceso en línea: | https://repositorio.unipampa.edu.br/handle/123456789/10514 |
| Access Level: | acceso abierto |
| Palabra clave: | ENGENHARIAS Engenharia elétrica Transformadores elétricos Sistemas de energia elétrica Correntes de Inrush Electtrical engineering Electrical transformers Electrical power systems Inrush currents |
| Sumario: | Also known as inrush current, magnetizing current arises during transformer energization. Due to its transient characteristics and high amplitude, this current can cause unwanted operations of protection relays, resulting in incorrect tripping. The main objective of this work is to compare different detection methods found in the literature, which are based on the analysis of differential current to distinguish transformer energization events from fault-related events. For this purpose, simulated datasets generated in PSCAD were used, and the methods were implemented and tested in the MATLAB environment. This study also proposes an approach based on the Synchrosqueezed Wavelet Transform (SWT) combined with the Bag of Features (BoF) model, evaluating its effectiveness under various operating conditions, such as diferente switching angles, fault inception times, and knee-point voltage levels of the magnetic saturation curve. The results highlight the importance of developing and applying accurate detection methods capable of precisely identifying inrush currents, minimizing false trips, and ensuring the reliability of protection systems. In this context, the proposed method — DIPI — achieved superior performance, standing out for its image-based classification strategy supported by SWT and BoF. |
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