Impacts of use PID control and artificial intelligence methods for solar air heater energy performance

Abstract

Solar air heaters generally operate at constant mass flow rates achieved with constant fan speed. This situation causes continuous energy consumption in solar air heater (SAH) systems. This study aims to reduce fan energy consumption by controlling the fan speed according to the outlet temperature of the SAH and, to obtain regression-based artificial intelligence models that can calculate the SAH energy efficiency value. For these purposes, the fan speed values of a SAH were modeled using three different system identification (SI) function models according to the set outlet temperature value. A proportional integral derivative (PID) control was applied to the SU function, which had fewer error values. The energy consumption of SAH, which worked with constant fan speed, was reduced by an average of 16% with the help of PID control application. In the second part of the study, a data set consisting of only environmental parameters (temperature, air velocity, solar radiation, relative humidity) was created for SAH's thermal efficiency value modeling. Using the data sets, mathematical equations that can calculate SAH energy efficiency were obtained with the help of regression algorithms (Pace and Elastic.Net). The obtained equations calculated the energy efficiency value with an error of 3%. The originality of this study is that a PID control was applied to a SAH system for the first time in the literature, and energy savings were achieved. In addition, utility models with equations calculating SAH energy performance only according to environmental parameters were obtained.