Robust Global Optimal Algorithm And Its Application In HTS-SMES

The progress in high temperature superconducting materials has given birth to High Temperature Superconducting Magnetic Energy Storage (HTS-SMES) Systems. Nowadays, the HTS-SMES has become a topical subject in electrical engineering and is being in the way of engineering applications thanks to the ever increasing requirement of modern power systems. However, so far there are a few works reported in literature relating to the integrated optimal design techniques of a HTS-SMES system.The improvements of Particle Swarm Optimization (PSO) methods are the first attentions of this dissertation. The improvements include the introduction of the "uphill" characteristics of a simulated annealing algorithm, and the crossover and mutation operations of a genetic algorithm. Therefore, the proposed PSO algorithm is more robust and efficient for fast global optimizations of electromagnetic devices, which is validated by its success in studying the optimal design problems of the HTS magnets.In order to compromise the solution quality and solution efficiency of the available stochastic optimal algorithms, the response surface model or methodology is introduced. In this regard, two different response surface models are proposed. The first one is based on an improved high dimensional Radial Basis Function by using the tensor product of MQ basis functions to stress exactly representation of the differences in the smoothness of the objective function along different coordinate directions. The second one is based on the Moving Least Squares (MLS) approximation and is firstly introduced to the computational electromagnetics community of China by the author. Both proposed RSMs are positively confirmed by the numerical results as reported.To solve extremely computationally heavy electromagnetic design problems such as a complex HTS-SMES system, fast and efficient hybrid global optimal methods based on the combination of RSM and stochastic algorithms are also lines of the study of the author. The optimal results on benchmark functions and practical optimizations of electromagnetic devices demonstrate that the proposed hybrid methods can not only reduce efficiently the number of function evaluations using FEA but also can find the global optimal solution.For the accurate and efficient determination of the electromagnetic fields and parameters of a HTS-SMES system, the mathematical models and methods of the electromagnetic fields, the storage electromagnetic energies, and inductance parameters of different HTS-SMES configurations including single solenoid, multiple parallel solenoids, and toroidal solenoid magnetic structures are extensively studied and developed. Especially, a high precision numerical model and method for a toroidal solenoid structure is firstly introduced in this dissertation.To facilitate and provide guidelines for engineering applications, comprehensive studies are conducted on a 35KJ/7KW HTS magnet, which has already been put into engineering application, and the aforementioned works are validated. By using the proposed PSOC global optimal algorithm, the 35KJ/7KW HTS magnet is further optimized successfully, and the concept design of a high level, i.e., a 300MJ/100 MW HTS magnet is explored.In the final, to increase the running current and therefore improving the storage capacity of the HTS-SMES magnet, the measures to decrease the radial component of the magnetic field in the end turns of the HTS-SMES magnet have been studied qualitatively and quantitatively.