Integrasi IoT pada Evaluasi Efisiensi Panel Surya Off-Grid pada Beban Resistif dan Induktif

Aripin Triyanto; Akbar Maulana; Joko Tri Susilo; Yoyok Dwi Setyo Pambudi

doi:10.22146/jnteti.v15i1.20351

Aripin Triyanto Electrical Engineering Study Program, Faculty of Engineering, Universitas Pamulang, Tangerang Selatan, Banten 15417, Indonesia
Akbar Maulana Electrical Engineering Study Program, Faculty of Engineering, Universitas Pamulang, Tangerang Selatan, Banten 15417, Indonesia
Joko Tri Susilo Electrical Engineering Study Program, Faculty of Engineering, Universitas Pamulang, Tangerang Selatan, Banten 15417, Indonesia
Yoyok Dwi Setyo Pambudi Electrical Engineering Study Program, Faculty of Engineering, Universitas Pamulang, Tangerang Selatan, Banten 15417, Indonesia

DOI: https://doi.org/10.22146/jnteti.v15i1.20351

Keywords: Solar Panel, Resistive Load, Inductive Load, Off-Grid, IoT

Abstract

Solar energy is one of the most widely utilized renewable energy sources, particularly in off-grid systems. However, its conversion efficiency is influenced by the type of load applied. Resistive and inductive loads exhibit different power consumption characteristics, thereby affecting the performance of solar panels. Therefore, an analysis is required to examine the impact of these load types on solar panel efficiency, supported by Internet of Things (IoT)-based monitoring for real-time data acquisition. This study aims to analyze the effect of resistive loads (incandescent lamps) and inductive loads (fans) on the efficiency of a 50 Wp off-grid solar panel system, as well as to evaluate the effectiveness of IoT in monitoring system performance. The methodology involved experimental testing by connecting the solar panel to both types of loads. The observed parameters included voltage, current, and power generated by the solar panel, as well as the power consumed by each load. Data were collected using sensors and transmitted to an IoT platform for remote analysis. The results indicate that resistive loads yield higher efficiency, ranging from 44.47% to 49.54%, compared to inductive loads, which only achieve efficiencies between 39.61% and 48.12%. The lower efficiency observed in inductive loads is attributed to reactive components that reduce the power factor and overall system performance. It can therefore be concluded that load type has a significant impact on the efficiency of off-grid solar panels, and the implementation of IoT has proven effective for real-time system performance monitoring.

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Integration of IoT in the Evaluation of Off-Grid Solar Panel Efficiency under Resistive and Inductive Loads

Abstract

References