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This research aims to monitor the performance of a 2x100Wp Solar Power Plant (PLTS) using the parameters of current, power, and solar intensity. The monitoring system is designed to record and analyze the electrical output of the solar panel in real-time. The experimental method is used by collecting data directly through current and voltage sensors, as well as light sensors connected to a microcontroller. Data was collected to see the relationship between solar intensity and electrical power generated. The test results show that the intensity of the sun greatly affects the amount of current and power generated by the solar panel. This monitoring system can be a tool for learning and analyzing the performance of small-scale solar power systems in a laboratory environment.

The aim of this study is to design a battery charging system using solar panels, integrated with an IoT-based monitoring system to improve efficiency and ease of supervision. The system utilizes the photovoltaic effect to convert solar energy into electrical energy, which is then stored in a battery through the regulation of a solar charge controller. The main components in this design include a solar panel, lead-acid battery, ESP32 microcontroller, current and voltage sensors, and the Blynk application for remote monitoring. The research method involves several stages, including the design of hardware such as solar panels, current and voltage sensors, and a step-down regulator, as well as software development using the Blynk platform and ESP32 programming. Test results show that the system is capable of achieving charging efficiencies between 89.45% and 99.57%, with optimal performance under clear weather and maximum sunlight conditions. The IoT system performs well up to a distance of 10–15 meters, with an average data transmission delay of less than 1.5 seconds. Therefore, this device proves to be effective as an independent battery charging and energy monitoring solution in locations without permanent electricity access.