An Efficient and High-Speed Disturbance Detection Algorithm Design with Emphasis on Operation of Static Transfer Switch

An Efficient and High-Speed Disturbance Detection Algorithm Design with Emphasis on Operation of Static Transfer Switch

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Static Transfer Switch (STS) is required for high-speed transfer of essential load to the alternate power source when the main source fails Classical Normal Tension due to power disturbance (PD).A fast and accurate PD detection method is required to ensure transfer time recommended by Computer Business Equipment Manufacturers Association (CBEMA) and IEEE Std.446.This study encompasses the machine learning technique to reduce detection time for the disturbance on the preferred source.

The 10 sample frames of acquired voltage signal were first differentiated and then distinctive features, i.e., Mean Absolute Deviation (MAD) and Energy (E) were extracted from the resultant frames.The features were fed to the Linear Support Vector Machine (L-SVM) classifier to detect the occurrence of PD events.

The proposed approach achieved 100% accuracy for PD detection and detection time was significantly reduced.The system is robust in terms of unbalanced and marginal PDs.The system was validated using both simulated and real voltage signals.The proposed algorithm is easy to implement Motor Tension Spring on an embedded system.

Hence, detection time according to STS requirements can be achieved under various power system conditions.