Multilevel Robust Design Optimization of a Superconducting Magnetic Energy Storage Based on a Benchmark Study
Superconducting magnetic energy storage (SMES) systems with different superconducting materials are attracting great attentions and funding from the governments around the world because they are promising large-scale energy storage devices for future smart grid. Due to the high cost of SMES, its manufacturing quality and operation reliability have to be investigated in the design optimization stage. This paper presents a robust design optimization method to solve this issue based on a benchmark problem, TEAM problem 22. The proposed method is based on a technique called design for Six Sigma. Meanwhile, a three-level optimization framework is employed to reduce the computation cost of a finite-element analysis due to high-dimensional design space and Monte-Carlo analysis. As shown, the manufacturing reliability and quality of the investigated SMES after robust optimization have been increased greatly.