Study on HTS SMES coil for optimized dimensions

Superconducting Magnetic Energy Storage(SMES) stores energy in the form of a magnetic field and is being used in many applications such as load-leveling, pulsating power supply, and instantaneous voltage drop compensation. Optimization of dimensions is required for reducing the refrigeration cost, c...

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Bibliographic Details
Published in:IEEE transactions on applied superconductivity 2023-10, Vol.33 (7), p.1-11
Main Authors: Anand, A., Gour, A. S., Datta, T. S., Rao, V. V.
Format: Article
Language:English
Subjects:
Coils
Electrical loads
Energy storage
High temperature superconductors
HTS SMES
Lenses
Leveling
Linear programming
Magnetic energy storage
Optimization
Solenoid
Stress
Superconducting magnetic energy storage
Superconducting magnets
Teaching Learning Based Optimization
Voltage drop
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Summary:Superconducting Magnetic Energy Storage(SMES) stores energy in the form of a magnetic field and is being used in many applications such as load-leveling, pulsating power supply, and instantaneous voltage drop compensation. Optimization of dimensions is required for reducing the refrigeration cost, cost of 2G HTS, structural support and cryostat dimensions. A generic objective function was developed for a fixed energy storage, with minimum length having von-Mises stress below the critical stress. A parameter-less, population-based optimization method i.e. Teaching Learning Based Optimization(TLBO) is used to obtain the dimensions of HTS coil. These HTS coils then can be stacked together to make the desired magnetic energy storage system. The effect of various dimensions on optimized length is studied and presented.
ISSN:1051-8223
1558-2515
DOI:10.1109/TASC.2023.3289092