Estimation of Machine Parameters in Superconducting Transformer using Differential Evolution. (July 2020)

• Record Type: Journal Article
• Authors: Yonenaka, T; Muraoka, T; Ichiki, Y; Otabe, E S; Tokunaga, Y
• Is Part Of: Journal of physics. Volume 1590(2020)
• Publication Date: 2020-07
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1590/1/012056
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: To analyze the inrush current in a superconducting transformer, the machine parameters for the transformer were estimated from the measured current using a search algorithm. To address the large rising edge error in estimations performed using a genetic algorithm (GA), a differential evolution (DE) was used in this study. As a result, the estimated time was reduced to about 1/10 that obtained with GA, and the evaluation value indicating the difference between the measured value and the estimated value was reduced to about 1/2. Thus, it was possible to estimate with higher accuracy by using DE.