{"title":"Hermetically sealed ecodesign distribution transformer weight optimization considering power losses and total ownership cost (TOC)","authors":"Mohammad Hassan Hashemi , Ulas Kilic","doi":"10.1016/j.prime.2025.100946","DOIUrl":null,"url":null,"abstract":"<div><div>This paper investigates the application of heuristic optimization techniques for weight optimization in eco-design distribution transformers, with a focus on hermetically sealed transformers. Specifically, the study employs Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) algorithms to compare their efficacy against conventional design approaches. Through rigorous analysis, GWO emerges as the superior method, showcasing enhanced performance in weight optimization. The findings underscore the significance of weight optimization in eco-design, as it directly contributes to resource conservation, including essential materials like copper, aluminum, oil, and iron. Consequently, the study highlights the pivotal role of heuristic optimization methods in advancing eco-friendly transformer design practices, with GWO demonstrating notable superiority in achieving weight reduction objectives.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"12 ","pages":"Article 100946"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772671125000531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper investigates the application of heuristic optimization techniques for weight optimization in eco-design distribution transformers, with a focus on hermetically sealed transformers. Specifically, the study employs Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) algorithms to compare their efficacy against conventional design approaches. Through rigorous analysis, GWO emerges as the superior method, showcasing enhanced performance in weight optimization. The findings underscore the significance of weight optimization in eco-design, as it directly contributes to resource conservation, including essential materials like copper, aluminum, oil, and iron. Consequently, the study highlights the pivotal role of heuristic optimization methods in advancing eco-friendly transformer design practices, with GWO demonstrating notable superiority in achieving weight reduction objectives.