Optimization Design of SMES Solenoids Considering the Coil Volume and the Magnet Volume

Solenoids can be simply built and provide highly stored energy per unit of the conductor. A novel two-objective optimization design model of the superconducting magnetic energy storage (SMES) solenoid system has been suggested. The objectives include the minimization of the solenoid coil volume and the whole magnets volume. Three constraints are considered, i.e., the energy requirement, the stray field in the surrounding region, and the quench condition. Non-dominant sorting genetic algorithm (NSGA-II) is adopted for the two-objective optimization. The probability-of-objective-comparing, p_obj, has been defined to improve the search ability, and an adaptive method has been proposed to control the parameter p_obj. The adaptive parameter control guarantees the exploration in the early stage and the exploitation in the late stage. Numerical experiment results show that the suggested model and the improved algorithm can provide a set of Pareto solutions for the optimization design of SMES solenoids.