Assessment of Data Acquisition System for Forecasting Temperature and Solar Irradiation

Data acquisition systems (DAQS) are the main instruments utilized in laboratory research by scientists and engineers for tests, measurement, and control. Generally, the DAQS are used from commercial, industrial, and custom components to digitize signals from the sensors and save this dataset for more analysis. In the power system, the DAQS is implemented for measuring solar irradiation, temperature, voltage, current, and power dispatch from the PV stations. Moreover, the DAQSs are widely integrated with PV systems to collect the dataset for evaluating system performance and different energy planning purposes. The aim of this paper is to evaluate DAQS connected with a PV system for building a forecasting model based on machine learning. The proposed system includes a DAQS, PV system, power converters, and power management components for monitoring the system under various operating conditions. The proposed DAQS is analyzing, monitoring, and constantly acquiring data without interruption, the output characteristics for the PV systems such as the temperature and solar irradiation. The DAQS is considered a feasible solution to collect the system dataset for analysis and forecast of the power dispatch from the PV system.