A GRNN Based Algorithm for Output Power Prediction of a PV Panel

Abstract

In this paper we investigated the reliability of a GRNN algorithm for the power prediction of a PV panel in order to minimize the effect of fast changing of the meteorological conditions. An experimental database of meteorological data (irradiance and module temperature) as input and electrical measure (power delivered by PV Panel) as output has been used. A database composed of two sets 97 values each one is used for training and validating the proposed GRNN model. The data used to develop the proposed algorithm are attained during two separated days from a PV panel within the MIS-Lab of UPJV, France. According to the gained results the algorithm can help to predict real instantaneous power even during temporary change in meteorological data.