Applications of fuzzy inference mechanisms to power system relaying

Most transmission line protective schemes are based on deterministic computations on a well defined model of the system to be protected. This results in difficulty because of the complexity of the system model, the lack of knowledge of its parameters, the great number of information to be processed, and the difficulty in taking into consideration any system variation as the rules are fixed. The application of fuzzy logic for exploring complex, nonlinear systems, diagnosis systems and other expert systems, particularly when there is no simple mathematical model to be performed, provides a very powerful and attractive solution to classification problems. In this paper, a feasibility study on the application of different fuzzy reasoning mechanisms to power system relaying algorithms is conducted. Those mechanisms are namely, Mamdani's mechanism, Larsen's mechanism, Takagi-Sugeno's mechanism, and Tsukamoto mechanism. A comparative analysis on the application of these fuzzy inference mechanisms to a novel fault detection and phase selection technique on EHV transmission lines is reported. The proposed scheme utilises only the phase angle between two line currents for the decision making part of the scheme. A sample three-phase power system was simulated using the EMTP software. An online wavelet-based preprocessor stage is used with data window of 10 samples (based on 4.5 kHz sampling rate and 50 Hz power frequency). The performance of the proposed model was extensively tested in each case of fuzzy inference mechanism using the MATLAB software. The advantages and disadvantages of each mechanism are reported and compared together. Some of the test results are included in this paper.