Journal of Mechatronics and Artificial Intelligence
Vol 1, No 2 (2024): JMAI: December 2024

Optimizing Energy-Efficient Home Electrical Systems through Capacitor Integration to Improve Future Energy Efficiency

Adi Nugraha (Universitas Sultan Ageng Tirtayasa)
Felycia Felycia (Universitas Sultan Ageng Tirtayasa)



Article Info

Publish Date
23 Dec 2024

Abstract

This research discusses the optimization of energy-efficient home electrical systems through the integration of capacitors to improve future energy efficiency. The main objective is to analyze the impact of installing power capacitors in parallel with electrical loads such as fans, refrigerators, and computers to improve power factor and reduce energy consumption. An experimental approach is used, installing capacitors with different values (2μF, 6μF, 8μF) on the test loads and measuring parameters such as voltage, current, power factor, and active power. The results show that the installation of optimal capacitors (e.g., 2μF for fans, 8μF for refrigerators) significantly improves the power factor, from around 0.55-0.61 without capacitors to near unity with capacitors. This power factor improvement reduces the current flowing through the system, leading to lower active power losses and increased energy efficiency. For example, the fan current is reduced from 0.197A to 0.109A with a 2μF capacitor. The active power consumption also decreased for some loads, such as fans experiencing a 4.8% reduction, indicating energy savings. The capacitor integration provides economic benefits through reduced electricity costs and environmental benefits by lowering carbon emissions from reduced electricity generation. The key is to carefully select the right capacitor size to avoid over-compensation, requiring an analysis of the reactive power requirements for each load

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Journal Info

Abbrev

JMAI

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

Description

The Journal of Mechatronics and Artificial Intelligence (JMAI) (E-ISSN 3048-4227 P-ISSN 3062-729X) serves as a platform for disseminating scholarly research related to the fields of mechatronics and artificial intelligence, as well as related sub-disciplines. We extend an invitation to researchers, ...