Analysis of Comprehensive Loss Model of Dry-type Transformer Based on Combined Objective Weighting Method

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.

Keywords

• aewoa
• comprehensive loss
• combined objective weighting method
• dry-type transformer
• power quality