Monitoring and enhancing the performance of PV systems using IoT and artificial intelligence algorithms | ||||
| ERU Research Journal | ||||
| Volume 3, Issue 1, January 2024, Page 950-964 PDF (688.67 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erurj.2024.241998.1080 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Ahmed Ali  1; Raafat El-Kammar2; Hesham Fathy Hamed3; Adel Elbaset4; Aya Hossam5
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| 1Department of Telecommunications Engineering, Faculty of Engineering, Egyptian Russian University, Egypt | ||||
| 2Electrical Eng. Department, Faculty of Eng. (Shoubra), Benha University, Egypt | ||||
| 3Artificial Intelligence, Dean of Faculty of Artificial Intelligence, Egyptian Russian University, Badr, Egypt/Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia, Egypt | ||||
| 4Department of Electromechanics Engineering, Faculty of Engineering, Heliopolis University, Cairo, Egypt | ||||
| 5Electrical Engineering Department, Faculty of Engineering (Shoubra), Benha University, Benha, Egypt | ||||
| 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. | ||||
| Keywords | ||||
| PV systems; Maximum power output; IoT; AI algorithms | ||||
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