Classification of high impedance fault using MWT and enhanced fuzzy logic controller in power system

This paper contains a new algorithm for High Impedance Fault (HIF) protection. The HIF is happen when a conductor touch a high impedance surface such as asphalt road, sand, cemented or tree. The main goal of this projected system is to recognize and categorize the HIF based improved system which is used to examine the amplitudes of voltage and current in the system is relatively insufficient and also progress the presentation of the power system. So, the area of defect classification and position regarded as removing characteristics that may aid from the temporary presentation of the voltage and current waveforms. In this document, multi wavelets transform (MWT) and enhanced fuzzy logic controller (FLC) are exploited to identify and categorize the HIF in the power system. Genetic algorithm (GA) is engaged for producing the regulations for fuzzy logic controller. Primarily, the characteristics of the power signal are removed by using the wavelet algorithm and the arithmetical metrics are intended. The calculated qualities are useful to the controlled learning technique and the worth of the signal is categorized. The learning technique, which is associated to the learning algorithm, inspects the data and differentiates the samples applied for the principle of categorization and weakening examination. FLC is employed to categorize the HIF in the power system and its fundamental structure is really not suitable for the rule of an extremely composite system since typically there are not adequate facts about the system obtainable. Consequently, a competent method is necessary to develop the presentation of FLC. Depend on these, the projected technique is executed in MATLAB/Simulink platform and its presentation is estimated and contrasted with other conventional techniques.