Hermetically sealed ecodesign distribution transformer weight optimization considering power losses and total ownership cost (TOC)

Mohammad Hassan Hashemi , Ulas Kilic
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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.
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考虑功率损耗和总拥有成本(TOC)的密闭式生态设计配电变压器重量优化
本文以密闭式配电变压器为研究对象,研究了启发式优化技术在配电变压器生态设计中的应用。具体来说,该研究采用差分进化(DE)、粒子群优化(PSO)和灰狼优化(GWO)算法来比较它们与传统设计方法的效果。经过严格的分析,GWO在权重优化方面表现出更强的性能,是一种更优的方法。研究结果强调了重量优化在生态设计中的重要性,因为它直接有助于资源节约,包括铜、铝、油和铁等重要材料。因此,该研究强调了启发式优化方法在推进环保变压器设计实践中的关键作用,GWO在实现减重目标方面表现出显着的优势。
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