The recent years have seen the growing demand of solar energy prompting a lot of academic as well as industrial interest in the optimization of solar energy generation. The monitoring systems of photovoltaic (PV) are critical in ensuring that the output is maximized. Internet of Things (IoT) technologies are converging, which is transforming the area of solar power and bringing new paradigms of managing energy. Combining these technologies with solar generation allows significant prospects of increasing scalability, flexibility, and efficiency. It offers the ability to enhance solar energy harvesting with data‐driven monitoring and tracking. This paper proposes an IoT‐enabled solar tracking framework which updates the panel orientation using real‐time cloud‐based solar data. The proposed architecture includes an interlinked simulation system that uses a Raspberry Pi to obtain information on a cloud‐based system. This information is synchronized with a servo motor–controlled mechanism to produce tracking commands for tilt and azimuth adjustment. A special interface has been created to pass the data. The data has been sent to a PV model integrated into MATLAB Simulink. Solar tracking systems have proved to be efficient in enhancing the performance of solar power generation due to the capabilities of the IoT integrated systems. The electrical performance of the PV system is simulated with the help of a MATLAB/Simulink model, which works based on real‐time data collection with the help of the IoT, and tracking control logic is realized with the help of a Raspberry Pi.
Narain et al. (Thu,) studied this question.
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