Volume 20 No 20 (2022)
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IoT Based Solar Charge Controller with Auto Adjustable Panel Using Image Recognition
Dinesh Kabra, Dr. Vinesh Agarwal
Abstract
Despite the increasing demand for PV energy, the output from panels and cells is often suboptimal due to the unpredictable nature of the environment. In this work, we focus on IoT connectivity, remote monitoring using an Android app, and graph plot visualization with our developed Python software. To address the variability in environmental conditions affecting PV output, we have developed an IoT-based solar charge controller (SCC) with remote monitoring capabilities. Our system utilizes IoT-based sensors to continuously monitor and upload vital performance data, such as voltage, current, and temperature, to the cloud. This data is then accessible in real-time, allowing for effective remote management and tracking. The incorporation of IoT technology facilitates proactive maintenance and quick troubleshooting, significantly enhancing the reliability and efficiency of the solar power system. The core of our system is the PIC16F73 microcontroller, which handles the power (MPPT) algorithm to ensure the solar panels operate at their optimal power output. The Android app we developed provides a user-friendly interface for monitoring the system’s performance, Additionally, our Python software offers advanced graph plot visualization, enabling detailed analysis of the system’s data over time. By leveraging IoT connectivity and robust remote monitoring tools, our solution not only optimizes the performance of photovoltaic systems but also simplifies the management process for users. This integration of technology ensures that PV systems can adapt to varying environmental conditions and continue to deliver efficient and reliable power.
Keywords
IoT, Charge Controller, Remote monitoring, Solar Charge Controller
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