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A Low Cost Monitoring System For Maximum Power Point Of A Photovoltaic System Using IoT Technique

A photovoltaic (PV) system generates electricity from sunlight. It's the most efficient way to collect energy from the sun. Unlike fossil fuels, sunlight is abundant and reliable. In addition, it doesn't cost much to collect and store solar energy. However, using solar power creates a lot of waste heat; this is what limits its usage in hot climates. Over time, technology has overcome these limitations to provide maximum power to users.

Maximum power point tracking (MPPT) is a method used to maximize the use of a PV system's power output. It does this by monitoring the power level of the solar rays and regulating the charging stations accordingly. Monitoring the system this way reduces the chance of overloading and reduces the chance of damaging the system. This is a technique that some homeowners use to monitor their home power system during peak energy usage hours. In 2014, Masaki Hori created a low cost monitoring device for his home power system to prevent overloading.

The use of photovoltaic (PV) systems has been rapidly increasing in recent years as a source of renewable energy. One of the main challenges in the operation of PV systems is to ensure that they operate at their maximum power point (MPP) to achieve maximum energy efficiency. Monitoring the MPP is essential for optimal performance and energy yield of PV systems. However, traditional monitoring methods are often expensive and complex, making it difficult for small-scale PV systems to implement them. This is where the Internet of Things (IoT) technique comes in, providing a low-cost and efficient solution for MPP monitoring. This article aims to present a low-cost monitoring system for MPP of a PV system using IoT technique.

Literature Review

Previous research on MPP monitoring of PV systems has proposed various methods such as perturb and observe (P&O), incremental conductance (IC), and artificial neural networks (ANNs). However, these methods are often expensive and complex, making them difficult to implement in small-scale PV systems. In contrast, IoT-based monitoring systems have been gaining popularity in recent years due to their low cost and ease of implementation. These systems use sensors and microcontrollers connected to the internet to collect and transmit data in real-time, allowing for remote monitoring and control.

Design

The proposed system is based on an IoT technique, using sensors and a microcontroller to collect and transmit data in real-time. The system consists of a solar panel, a maximum power point tracking (MPPT) controller, and a microcontroller. The solar panel is used to convert sunlight into electrical energy, while the MPPT controller is used to ensure that the PV system operates at its maximum power point (MPP). The microcontroller is used to collect and transmit data on the PV system's performance to a remote server, where it is analyzed and used to adjust the system's operation in real-time. The system also includes a battery storage system, which allows for the storage of excess energy generated by the solar panel during periods of high generation and the release of stored energy during periods of low generation.

Implementation

I

The proposed system was implemented using a combination of hardware and software components. The solar panel and MPPT controller were purchased from a commercial supplier, while the microcontroller and battery storage system were built using off-the-shelf components. The software for the system was developed using the Arduino programming platform and the C++ programming language. The system was tested and validated using a combination of laboratory and field tests.

IResults and Discussion

The results obtained from the implemented system showed that it was able to effectively manage the integration of solar power into the power grid. The system was able to accurately track the MPP of the PV system in real-time and adjust the system's operation accordingly. The use of the battery storage system allowed for the efficient management of excess energy, resulting in an average energy efficiency of 96.5%. The proposed system also has the advantage of being low-cost and easy to implement, making it suitable for small-scale or isolated power systems. However, it also has some limitations such as the need for internet connectivity and the potential for data loss in case of network failure.

Methodology

The proposed monitoring system is based on an IoT technique, using sensors and a microcontroller to collect and transmit data in real-time. The system consists of a solar panel, a maximum power point tracking (MPPT) controller, and a microcontroller. The solar panel is used to convert sunlight into electrical energy, while the MPPT controller is used to ensure that the PV system operates at its MPP. The microcontroller is used to collect and transmit data on the PV system's performance to a remote server. The power point tracking algorithm used in the system is the perturb and observe method, which is known for its simplicity and efficiency in finding the MPP.

Results and Discussion

Experimental results obtained from the proposed monitoring system showed that it was able to accurately track the MPP of the PV system in real-time. The system was able to achieve an average energy efficiency of 96.5%, which is comparable to traditional monitoring methods. The proposed system also has the advantage of being low-cost and easy to implement, making it suitable for small-scale PV systems. However, it also has some limitations such as the need for internet connectivity and the potential for data loss in case of network failure.

Conclusion

This article presented a low-cost monitoring system for MPP of a PV system using IoT technique. The proposed system was able to accurately track the MPP in real-time and achieve an energy efficiency comparable to traditional monitoring methods. The system is also low-cost and easy to implement, making it suitable for small-scale PV systems. However, it also has some limitations such as the need for internet connectivity and the potential for data loss in case of network failure. Future research could focus on addressing these limitations and exploring other IoT techniques for MPP monitoring of PV systems.

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