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IoT-based low-cost prototype for online monitoring of maximum output power of domestic photovoltaic systems

  • Rouibah, Nassir (Electric and Industrial Systems Laboratory, Faculty of Electronics and Informatics, USTHB University) ;
  • Barazane, Linda (Electric and Industrial Systems Laboratory, Faculty of Electronics and Informatics, USTHB University) ;
  • Benghanem, Mohamed (Physics Department, Faculty of Science, Islamic University) ;
  • Mellit, Adel (Faculty of Sciences and Technology, Renewable Energy Laboratory, Jijel University)
  • Received : 2019.12.03
  • Accepted : 2020.10.15
  • Published : 2021.06.01

Abstract

This paper presents a low-cost prototype for monitoring online the maximum power produced by a domestic photovoltaic (PV) system using Internet of Things (IoT) technology. The most common tracking algorithms (P&O, InCond, HC, VSS InCond, and FL) were first simulated using MATLAB/Simulink and then implemented in a low-cost microcontroller (Arduino). The current, voltage, load current, load voltage, power at the maximum power point, duty cycle, module temperature, and in-plane solar irradiance are monitored. Using IoT technology, users can check in real time the change in power produced by their installation anywhere and anytime without additional effort or cost. The designed prototype is suitable for domestic PV applications, particularly at remote sites. It can also help users check online whether any abnormality has happened in their system based simply on the variation in the produced maximum power. Experimental results show that the system performs well. Moreover, the prototype is easy to implement, low in cost, saves time, and minimizes human effort. The developed monitoring system could be extended by integrating fault detection and diagnosis algorithms.

Keywords

Acknowledgement

We would like to thank the deanship of scientific research at Islamic University of Madinah, Saudi Arabia for the financial support of this work through the program Tamayouz 2 of the academic year 2020/2021, research project No. 489.

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