Prototype of a mini wind turbine for automatic charging based on the Internet of Things (IoT) in the garden area of STMIK Kaputama

Deva Ryandi; Achmad Fauzi; Husnul  Khair

doi:10.59934/jaiea.v6i1.2798

Authors

Deva Ryandi STMIK Kaputama
Achmad Fauzi STMIK Kaputama
Husnul Khair STMIK Kaputama

DOI:

https://doi.org/10.59934/jaiea.v6i1.2798

Keywords:

Automatic charging, Blynk, ESP32, Garden lamp, Internet of Things, Mini wind turbine

Abstract

Lighting in the garden area of STMIK Kaputama Binjai, located on the upper floor of the building, remains very limited and fully dependent on the conventional power supply, making the area uncomfortable and potentially unsafe for use at night. This research aims to design and build a mini wind turbine prototype as an alternative energy source for garden lamps, to develop an automatic charging system that stores wind energy in a battery and switches the lamp on based on a light sensor, and to implement Internet of Things (IoT) technology through the Blynk application for remote monitoring and control. The research was developed using the prototype method, with a system consisting of a vertical axis wind turbine (VAWT) coupled to a 12 V DC generator, a 1N5822 Schottky diode, an LM2596 module, a TP4056 module as the charging controller for an 18650 battery, an XL6009 module as a step-up converter for the LED lamp, a voltage sensor, an INA219 current sensor, an LDR sensor, a relay, and a NodeMCU ESP32 as the main controller. Testing was conducted directly in the garden area of STMIK Kaputama using naturally available wind. The results show that the prototype produced 0.11-2.62 W of power at wind speeds of 1.8-5.3 m/s, the automatic charging system raised the battery voltage by 0.48 V (from 3.62 V to 4.10 V) over three hours, the LDR-based automatic lighting control succeeded in all five lighting conditions (100%), the charged battery powered the lamp for more than six hours, and real-time monitoring via Blynk operated with an average delay of 1.40 seconds with remote ON/OFF control succeeding in 10 out of 10 attempts, supported by an average error of 1.74% for the voltage sensor and 3.06% for the INA219 current sensor. Therefore, the IoT-based mini wind turbine prototype is proven capable of serving as an independent and environmentally friendly alternative energy source for campus garden lighting, although the charging rate is still affected by fluctuations in local wind speed.

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