Sistem Monitoring Solar Charge Controller Menggunakan Raspberry Pi 3 Secara Mobile

Authors

  • Aldo Kris Barlianto Program Studi Informatika
  • Djoni Haryadi Setiabudi Program Studi Informatika
  • Resmana Lim Program Studi Teknik Elektro

Keywords:

Pemaknaan pengalaman, komunikasi keluarga, suami istri, pemeliharaan hubungan, postpartum depression

Abstract

In monitoring the charging of power source using solar panels, it is very important to find out the process of charging resources. Research about monitoring process has been carried out previously, but the monitoring process still depends on other software, and it cannot be done by mobile. In this research, the monitoring of solar charge controller will be carried out where user is no longer depends on additional applications / software and also can be done via PC / smartphone.
The solar charge controller itself comes with a factory default software for data monitoring, but the usage of the application is very limited to the wiring system and also the monitoring process cannot be carried out by mobile. This research aims to be able to carry out the monitoring process by mobile using Raspberry Pi, so that users are no longer limited by wiring system and monitoring can be done in application which based on mobile web application, so that users can find out the monitoring process from a website on a desktop and also via smartphone.
Through several test that has been held, it can be concluded that monitoring process can be done online using Raspberry Pi and modbus rs485 devices in mobile web application. The power parameters taken by the application are solar voltage, solar current, battery voltage, charge current, and load power. The application is also able to run / monitor several existing devices or more than one device in one application. During testing process, it is using 1 scc device and for other devices using a virtual device. The result of the percentage error from the measurement of the monitoring device is the reading of the solar voltage parameter data has an accuracy rate of 99.26% with an average 0.1 V selection, solar current has an accuracy rate of 95.6% with an average difference of 0.03, and the battery voltage has an accuracy 96.31 with an average difference of 0.18V.

References

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Published

2021-04-10

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Articles