XOptimal design of power transformers using quantum-behaved particle swarm optimization

This paper addresses the transformer design optimization(TDO) problem which is a complex mixed integer nonlinear problem. Firstly, the enumeration method, which is the most robust method to find the global optimal solution, is researched to solve TDO problem. The low computation efficiency makes the enumeration method difficult to be used in industry. Quantum particle swarm optimization(QPSO) is then introduced to improve the computation efficiency, and meanwhile a new constrain handling method is proposed for multi-constrains problems. Based on the calculated results of the enumeration method, the control parameter of QPSO is analyzed under both fixed value strategy and linear variation strategy. According to the calculated results, some conclusions concerning the selection of the control parameter are drawn. The case study shows that the computation efficiency of QPSO is far better than the enumeration method. Meanwhile QPSO keeps an excellent ability to find the optimal solution.