With the increasing need and awareness for using efficient and sustainable energy resources, solar energy has emerged as a key alternative to traditional energy sources, and its widespread adoption requires the development of an advanced solar monitoring and data acquisition system. This report presents a solar monitoring system that will provide real-time data monitoring on various solar panel parameters, which provides insights for maintaining the efficiency and productivity of the solar panel output. The model is designed on a rooftop college solar panel in which of two solar PV panels connected together in series connection. Based on the panel parameters and specifications, the sensing elements for the system are decided. These sensing devices sense the various system parameters at a given time interval and send them to a cloud for the storage of data with the help of the microcontroller. Simultaneously, the data is displayed with the help of an IOT platform for the users. In the study, the model of the monitoring system was tested at various time intervals throughout the daytime, and the outcome was achieved. This system works on a microcontroller which is a Wi-Fi-enabled module that enables data storage and representation. Smart Solar Monitoring and Data Acquisition Systems provide real-time access to data, allowing operators to make informed decisions promptly, enhancing system efficiency, and enabling remote monitoring.
Introduction
As India’s energy demand grows with its population, it is turning increasingly toward renewable energy sources, particularly solar energy, to meet its climate and sustainability goals. With a total installed capacity of 400 GW, of which 40% comes from renewables, India ranks third globally in renewable energy production. Following the COP26 climate summit, India committed to achieving net zero emissions by 2070 and sourcing 50% of its energy from renewables by 2030.
Objective
To support this transition, especially the growing use of rooftop solar systems, a smart solar monitoring and data acquisition system was developed. This system aims to:
Improve the efficiency and performance of solar panels.
Provide real-time monitoring of various environmental and electrical parameters.
Support data-driven maintenance and long-term analysis for solar systems.
Methodology
The system monitors two sets of parameters:
System parameters: voltage, current, solar panel temperature.
Environmental parameters: solar intensity, ambient temperature, atmospheric humidity.
A custom electrical circuit was designed and implemented with data collected over time for future analysis. Observations were made on how load, temperature, time, and light intensity affect solar power generation.
Key Components
Sensors Used:
ACS712 for current
EC-2173 for voltage
DS18B20 for panel temperature
DHT11 for ambient temperature & humidity
TCL25911 for light intensity
Microcontroller: ESP8266, Wi-Fi-enabled for cloud connectivity.
Data Handling:
Sensor data is calibrated and converted into standard units.
Data is uploaded in real-time to Microsoft Excel via OneDrive using HTTP GET requests and Google App Script.
Visualization & User Interface
Blynk App is used for real-time visualization of sensor data.
Displays parameters via graphs and gauges.
Offers remote monitoring using a user-friendly mobile interface.
Observations
Voltage and current output of solar panels are directly influenced by:
Sunlight intensity
Load connected
Ambient temperature and humidity
The collected data provides valuable insights into system behavior and performance under varying environmental conditions.
Conclusion
In this paper, a solar monitoring and data acquisition system is developed on a rooftop stand-alone PV system. It tracks the parameters of the solar panel such as voltage, temperature, humidity, current and light intensity. The data is sensed through various sensors, and collected by a microcontroller ESP8266 which stores live data in a database. The system constantly updates the database with new values and stores it in Microsoft Excel sheets which is used as a cloud storage platform using the OneDrive feature that can be accessed from various devices remotely using an internet connection. For better visualization, an IoT-based platform Blynk is used which gives a graphical representation by efficiently analysing any inconsistency in the data generated thus detecting various issues in the PV system. This user-friendly system will facilitate better monitoring of the PV array and timely maintenance by the user.
References
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