Design and Realization of Controller for Static Switch in Microgrid Using Wavelet-Based TSK Reasoning

A microgrid may comprise several zones with local loads and distributed generation resources. If a fault occurs in a zone, then a static switch between the faulty and fault-free zones must be activated to detect/classify the faults and enable the breaker to open the circuit immediately. This paper presents a new method for designing a detection/classification module in a static switch using the Park Transform (PT), Multiresolution Analysis (MRA) and Takagi-Sugeno-Kang (TSK) fuzzy rules. Both wavelet coefficients/energies of the d-axis component, within 0.96-1.92 kHz, obtained by MRA and PT are employed to effectively detect and classify the fault types using the local fault signals near the static switch without a complicated communication system. The proposed TSK fuzzy rules, defined by the scenario data only, successfully classify the faults. The proposed method is verified by hardware-in-the-loop simulation using a real-time digital simulator and a realistic 5 kVA static switch. The proposed method is implemented in a Xilinx field-programmable gate array. Test results show that the proposed method is efficient in the real-time control environment of a microgrid.