Abstract: Power distribution systems play vital role in providing electricity to the needs of industries and households. With diversity in power generation systems, power distribution became increasingly complex and prone to various issues such as quality, harmonics, line to line fault, line to ground fault and switching. In this paper, a hybrid power distribution system is simulated. It is made up of the power sources from wind power plant and photovoltaic system. Both are integrated to a power grid with the help of point of common coupling devices. The system is built using MATLAB Simulink and simulated it for generating data. Afterwards, Wavelet Transform (WT) is used to obtain different features from the negative sequence component at point of common coupling. They include loading of the hybrid system, standard deviation (SD) and energy content of WT coefficients of negative sequence voltage signal at different levels such as level 3 and level 4. Then, Artificial Intelligence (AI) based technique known as Artificial Neural Network (ANN) is trained with the collected features. Based on the knowledge gained from the features, the ANN is able to predict various faults associated with the hybrid power distribution system. The empirical study revealed that the system is capable of identifying different problems so as to improve the quality of power distribution system using AI based algorithm.
Keywords: Hybrid power distribution system, artificial intelligence, artificial neural network, power quality improvement
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