Analysis of Artificial Intelligence Based MPPT in PV Grid Connected System

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Bandana Gautam, Shivam Singh, Rajnish Bhasker


The There has been a rise in the demand for electrical power during the past 10 years. Installing a new power generator (PG) is a costly and time-consuming procedure. For this reason, solar power plants are considered a viable alternative for meeting the current energy demand. But crucial maintenance and output power balance are the key issues facing solar power facilities. In order to reduce output power balance and maintenance problems in solar plants, an appropriate approach is required. This study offers a novel method for tracking the maximum power for hybrid photovoltaic (PV) and wind energy systems (WES): single maximum power point tracking, or MPPT. In the proposed MPPT technique, a radial basis function network (RBFN) control mechanism is based on an artificial neural network (ANN).

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