Artificial intelligence based forecasting & optimization of solar cell model.

Abstract This work describes a number of soft-computing based solar forecasting techniques that facilitate the modelling of newly installed solar cell. The solar cell model is developed and validated against measured data. Prediction of solar radiation of a particular location depends upon number of inputs. So selection of most relevant input parameters is an important task for getting good predictions. The input parameters of the model used in this paper are sunshine duration, temperature, humidity where as the clearness index is considered as an output parameter. The magnitude of active current associated with PV inverter has been finalised by the solar based irradiation. The reactive current associated with the PV based inverter is controlled through the optimised solar radiation. [ABSTRACT FROM AUTHOR]