Monitoring and enhancing the performance of PV systems using IoT and artificial intelligence algorithms

Abstract

Monitoring and enhancing the performance of PV systems is a critical criterion for PV power plants. Hence, in the present paper, a smart prototype of the IoT technique and AI algorithms (here PSO) were used to achieve monitoring and enhancing performance of PV systems. A smart IoT technique based on embedded system through Node MCU ESP8266 has been constructed to monitor the solar power irradiance of solar cell systems. The measured results were displayed by ubidots through the HTTP protocol. Meanwhile, enhancing the performance of PV system is carried out using the PSO algorithm. The measured solar power irradiance was inlaid to the MATLAB simulation program as hardware in the loop to estimate the current, voltage, and output power in order to study the performance of the proposed PSO algorithm. Many improvements were carried out on the conventional PSO algorithm by a continuous modulation of the duty cycle to harvest maximum power output for long hours daily. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system and the achieved power output using the improved PSO made them a strong candidate for enhancing the performance of PV systems.