Virtual Instrumentation Applied to Identifying Parameters of Solar Radiation and Ambient Temperature Using Autoregressive Modeling with Exogenous Inputs

This work describes a mathematical model developed to identify solar radiation and ambient temperature patterns in Bogota, Colombia, using autoregressive modeling with exogenous inputs (ARX). The solar radiation data and temperature used in the model were taken from the meteorological stations of Universidad de Bogotá Jorge Tadeo Lozano and Instituto de Hidrología, Meteorología y Estudios Ambientales – IDEAM from Colombia; for a period of 5 years (2011-2015). The model (ARX) was implemented using the LabVIEW graphical programming language, and allow identification of solar radiation parameters using techniques MSE. After applying the ARX model, the results showed that the correlation between the solar radiation measured by the monitoring station and evaluated by the algorithm was 86.64%; while for the temperature was 76.15% for the same period. This type of parameter identification is for application in the field of photovoltaic solar energy as it might be possible to identify future capabilities of generating electricity with solar panels.