Multi-objective Optimization of 2G-HTS Coil for Magnetic Energy Storage System Using NSGA-II Algorithm

Superconducting magnetic energy storage (SMES) offer a promising solution to address the stability challenges associated with integrating renewable energy sources into electrical grids. In this study, we propose an optimal design for a double pancake superconducting coil using the NSGA-II algorithm. The coils are composed of second-generation high- temperature superconductors (2G-HTS). The problem is formulated a mixed variable optimization problem with 4 decision variables and 2 fitness functions which are the total energy stored and the mechanical stress of the coil. The decision variables are the total length of the coil, the inner radius of the coil, the distance inter pancakes and the width of the tape. Mathematical models for energy and mechanical stress are implemented in a MATLAB function. The optimization code is developed using the well-known pymoo framework in Python programming language. This code utilizes the MATLAB engine to make multiple calls to the MATLAB function for fitness evaluation within the Python environment. The Pareto set illustrates the best trade-off between the two fitness functions, while the corresponding variables span the search space. Among the search space variables for the double pancake at 77°K, the configuration featuring a 500 m long, 12 mm wide YBCO tape with an inner radius of 110 mm and an inter-pancake distance of approximately 20 mm exhibits the most interesting results at the elbow of the Pareto front. This configuration achieves an accumulated energy of 1.4 kJ and a mechanical stress of 600 MPa.

• BAGAN G. Steve Sèdjro

Mots clés de JLST

Mots clés de l'auteur
2G-HTS; Energy stored; NSGA-II; SMES coil; mechanical stress

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