Fusion of Signal Processing Techniques to Design Current and Voltage Features Based Protection Scheme for Utility Grid With Renewable Energy Penetration

This paper used fusion of Hilbert transform (HT), Stockwell transform (ST) and Alienation coefficient to design a protection scheme for utility network with high concentration of renewable energy (RE) generation. A hybrid fault detection index (HFDI) is designed which detects the fault events utilizing the features extracted from both current and voltage signals. Peak magnitude of HFDI is compared with a threshold magnitude (HTM) to detect fault events and discriminate such events from operational events. Faults are classified based on faulty phase numbers and a hybrid ground fault index (HGFI). Zero sequence voltage and zero sequence current are processed by application of ST to compute HGFI which effectively detects presence of ground during fault event. Performance of protection scheme is validated using utility grid of IEEE-13 bus test system where 50% RE penetration is used. Further, performance is also tested to detect faults incident on a practical utility network with RE penetration of 57%. Performance of algorithm is evaluated to recognize different fault events and operational events. Protection scheme is effectively tested to detect faults with high noise levels of 20 dB SNR (signal to noise ratio). Proposed protection scheme perform better compared to Alienation coefficient based protection scheme reported in literature.