Designing Power Transformer Using Particle Swarm Optimization with Respect to Transformer Noise, Weight, and Losses

Pramono, Wahyudi Budi and Wijaya, Fransisco Danang and Hadi, Sasongko Pramono and Wahyudi, Moh Slamet and Indarto, Agus (2023) Designing Power Transformer Using Particle Swarm Optimization with Respect to Transformer Noise, Weight, and Losses. Designs, 7 (1). ISSN 24119660

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Abstract

The increased use of electrical energy will encourage the installation of more power transformers in residential areas as well as in industrial areas. Each power transformer, in its operation, will generate noise that can interfere with comfort and, at some level, cause health problems. The design of the power transformer currently focuses on optimizing its economic side, so noise has not been considered at this design stage. This research is about optimizing the low noise transformer design. The main goal is to obtain a low noise power transformer with low production costs. The method used in this optimization is particle swarm optimization with a multi-objective function. The objective function consists of the minimization of load noise, core weight, and winding weight. In this study, 11 optimized variables were used. Some variables that are optimized must be in the form of integers. Therefore, the optimization process needs a mechanism for mapping variables. The results showed that a low noise power transformer could be designed at optimal cost. Design validation was performed analytically and numerically with COMSOL software. The optimization results showed a decrease in load noise, core, and winding weight by 0.86 dB, 2.12%, and 47.46%, respectively. The results of this optimization are better than the designs used regularly in the industry.

Item Type: Article
Additional Information: Library Dosen
Uncontrolled Keywords: load noise; transformer; optimization; particle swarm optimization; design
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Engineering > Electronics Engineering Department
Depositing User: Rita Yulianti Yulianti
Date Deposited: 02 Jul 2024 06:35
Last Modified: 02 Jul 2024 06:35
URI: https://ir.lib.ugm.ac.id/id/eprint/232

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