A Support Vector Machine-Based Power Transformer Differential Protection
support vector machine, power transformer, differential protection, CT saturation, wavelet transform
Power transformers play a major role in power systems operation, interconnecting generation, transmission, and distribution systems. Typically, the phasor-based differential protection is used as primary protection to this equipment. However, conventional power transformer differential protection can still face issues dealing with some types of events, such as faults during current transformer (CT) saturation, evolving faults, and inrush currents during an internal fault, to name a few. Over the last years, many works based on digital signal processing techniques and machine learning algorithms have been proposed in the literature to deal with these problems. This work proposes a power transformer differential protection scheme based on support vector machines (SVM) combined with high-frequency features extracted with the real-time boundary stationary wavelet transform (RT-BSWT). SVM models are derived with synthetic data, considering a wide variety of events, such as inter-turn faults, external faults during CT saturation, and evolving external-to-internal faults. A comparative performance assessment with the conventional protection is carried out, considering accuracy and other reliability indices, as well as operating time, and good results were achieved.