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Analysis of Comprehensive Loss Model of Dry-type Transformer Based on Combined Objective Weighting MethodSHAO, L. , WANG, S. , LIU, H. , LI, J. , LI, C. |
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Author keywords
AEWOA, comprehensive loss, combined objective weighting method, dry-type transformer, power quality
References keywords
power(15), transformer(12), optimization(7), systems(5), algorithm(5), type(4), transformers(4), distribution(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2024-08-31
Volume 24, Issue 3, Year 2024, On page(s): 45 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2024.03005
Web of Science Accession Number: 001306111400005
SCOPUS ID: 85202998978
Abstract
In this paper, the comprehensive loss of a dry-type transformer under the influence of power quality is objectively and reasonably analyzed. A combined objective weighting method based on Adaptive Average Pooling Enhanced Whale Optimization Algorithm (AEWOA) is proposed. Four objective weighting methods were utilized to calculate the foundational weights, aiming to circumvent the potential impact of subjective factors on the weighting process. The AEWOA incorporates an enhanced pooling mechanism to accelerate convergence towards the optimal population, thereby improving the efficiency of the algorithm in locating the global optimum. Extreme difference maximization is utilized as the objective function to ensure that a significant degree of differentiation is maintained among the linear combination coefficients. As a result, a comprehensive loss calculation model is established under the influence of power quality. The contrast experiment showcases the model's proficiency in lightweighting, emphasizing its superiority over the superimposed loss calculation method. This underscores the model's rationality and efficacy compared to traditional approaches. The model is valuable for calculating and analyzing the thermal load of dry-type transformers. |
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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