An improved parametrical optimization of superconducting energy storage rings via quantum particle swarm optimization approach

Nordin, Nurul Syazana (2022) An improved parametrical optimization of superconducting energy storage rings via quantum particle swarm optimization approach. [Project Paper] (Submitted)

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Abstract

A new improved version of an Intelligent Particle Swarm Optimization (IPSO) algorithm, is applied for the design of a Superconducting Magnetic Energy Storage (SMES) device. Quantum inspired particle swarm optimization (QPSO) is widely used global convergence algorithm for complex design problems. This algorithm is a population based optimal method and very simple in both theory and numerical implementation. Nowadays, it has been recognized as a paradigm for numerical optimizations. In 1996, a superconducting magnetic energy storage arrangement was selected to become a benchmark problem for testing different optimization algorithms, both deterministic and stochastic ones. Since the forward problem can be solved semianalytically by Biot Savart’s law, this benchmark became quite popular. In this paper, a new version of the design TEAM benchmark 22 will be made and some results will be presented.

Item Type:	Project Paper
Faculty:	Fakulti Sains
Depositing User:	Ms Emelda Mohd Hamid
Date Deposited:	10 Jun 2024 03:47
Last Modified:	09 Aug 2024 08:44
URI:	http://psaspb.upm.edu.my/id/eprint/1781

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