Improving efficiency of Photovoltaic System with Neural Network Based MPPT Connected To DC Shunt Motor
Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2013, Vol 3, Issue 5
Abstract
A photovoltaic generator exhibits nonlinear voltage-current characteristics and its maximum power point varies with solar radiation. A boost converter is used to match the photovoltaic system to the load of dc shunt motor and to operate the pv cell array at maximum power point. This paper presents an application of a neural network for the identification of the optimal operating point of pv module maximum power tracking control. The output power from the modules depends on the environmental factors such as solar insolation, cell temperature, and so on. Therefore, accurate identification of optimal operating point and continuous control of boost converter are required to achieve the maximum output efficiency. The proposed neural network has a quite simple structure and provides a highly accurate identification of the optimal operating point and also a highly accurate estimation of the maximum power from the PV modules. This model is simulated in matlab/simulink and results are obtained.
Authors and Affiliations
J. Reddy, B Manjunatha
Keywords
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- EP ID EP152000
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