Abstract

In recent times, it has been observed that the implementation of well-organized Distribution Systems are the back bone of smart grids. Further, the need of the hour is to realize a more flexible system involving energy savings and favorable environmental factors leading to development of Distributed Generation Systems (DGs). Such systems are expected to play an important role in efficient operation of Electric Power Systems. In this context, efforts are made to determine the effect of DGs on the electrical distribution networks. Different Electrical configurations of asynchronous generator - wind turbines have been considered leading to an algorithm developed to determine the influence of optimally placed DGs at various buses in the system. The behavior of the system is analyzed through different Power Quality Indices (PQIs), which are calculated by applying probability concepts, that overcome the limitations associated with traditional methods of calculating the Total Harmonic Distortion (THD). Additionally, a new PQI based on Total Demand Distortion (TDD) is also presented. An intelligent control algorithm based on machine learning concepts is incorporated, enabling to initiate power quality improvement/control strategies to be adopted by the distribution manager. A 17-bus test system is considered and modeled using Open Distribution System Simulator (OpenDSS). The results obtained are analyzed by MatLab - OpenDSS Component Object Model (COM) interface. The efficacy of the results is imminent based on a comparison with similar results obtained by the authors in the related literature.

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