双馈风力发电机混合粒子群优化设计

针对双馈风力发电机交流励磁电磁特性和变速恒频运行特点，从转子电压、转子容量、转子铁耗等方面探讨了该电机的电磁设计特点，并结合风力发电应用领域特点及要求，分别选取电机有效材料成本、额定效率及效率曲线平坦性为优化目标，建立了电机优化设计模型，继而提出了一种混合粒子群优化算法，通过引入基于适应度值的个体模糊惯性权重和基于种群多样性的自适应变异，提高算法处理多峰值非线性优化问题的能力，以实现双馈风力发电机优化设计．电机优化设计实例结果表明，与标准粒子群算法相比，提出的混合粒子群算法动态平衡了全局和局部搜索能力，收敛速度较快，寻优精度较高且不易陷入局部最优，同时各种优化目标下的双馈风力发电机设计优化结果较为理想，对于多峰值非线性优化问题不失为一种新的解决方法．

A Hybrid Particle Swarm Optimization Algorithm for Optimum Electromagnetic Design of DFIG-Based Wind Power System

Considering its AC excited electromagnetic characteristic and variable-speed constant-frequency operating characteristic in wind power applications,a thorough analysis of the doubly-fed induction generator(DFIG)design features is made in terms of rotor voltage,capacity and iron losses etc.A DFIG optimum design model is then built with effective material cost,rated efficiency and efficiency curve flatness separately selected as the optimization ob-jective.On this basis,a hybrid particle swarm optimization(HPSO)algorithm is proposed,in which a fitness-guided individual fuzzy inertia weight and a diversity-guided adaptive mutation are introduced to improve searching perform-ance.The optimization results of a DFIG design example show that compared with the standard particle swarm opti-mization(SPSO)algorithm,the proposed HPSO algorithm,which not only properly balances the global and local searching ability but also takes on quick convergence,high precision and even the absence of premature convergence,can better achieve the DFIG optimum design under different optimization objectives.That means that the proposed HPSO algorithm is applicable to the multi-model nonlinear optimization problems,especially for the DFIG optimum design.