Abstract
The planning and operation of distribution system requires the values of voltage magnitude at different sections of the system. Penetration of Distributed Energy Resources (DERs) in the power system improves the voltage profile especially during the peak load periods. The DERs in the conventional power system provides more options for voltage control mechanisms. The voltage control mechanism will be chosen based on the voltage profile of a particular section during given time period. Hence it is essential to estimate and update the voltage magnitudes of the system at pre specified time intervals. Many methods have been proposed to estimate the voltage profile of a radial distribution system. This paper proposes a new method for voltage profile assessment using Generalized Regression Neural Network (GRNN). The proposed method uses the influential load as inputs to estimate the voltage magnitudes with lesser computation time.
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