Control of PV Panel System Temperature Using PID Cuckoo Search

Abstract

In this study, the PV panel behavior as a nonlinear system had been studied well. The main contribution of this work was cooling the PV panel temperature to get the optimal power using a PID-CSA controller which was never employed previously in this application. In the beginning, the system has been modeled using three artificial neural network methods which are NARX, NAR and nonlinear input output based on MSE. Then, the PID controller with the intelligent cuckoo search algorithm technique had been studied to accustom PID controller parameters () based on MSE, ASE and IAE. The results exhibited that the best modeling method was NARX with 0.2255 MSE. On the other hand, all the controlling methods were effective and showed an excellent ability to control the system; however, the best method was based on MSE with an error equal to 2.578.