【作者】 王慧敏；

【导师】 夏长亮；

【作者基本信息】 天津大学 ， 电机与电器， 2010， 博士

【摘要】 双馈发电机转子交流励磁,因励磁电流频率、幅值和相位可控,具有功率调节灵活、调速性能优良及励磁容量小等优点,成为目前变速恒频风力发电技术应用和发展的主要机型之一。有效的励磁控制策略是实现双馈风力发电系统优越运行性能的关键,而双馈发电机良好的电磁特性及工作特性是实现励磁系统有效控制的前提。因此,双馈风力发电机励磁控制与优化设计研究对于风电技术进步和风电产业发展具有重要意义。本文围绕双馈风力发电机励磁控制易受系统不确性影响的问题,建立了双馈风力发电机空载及发电运行状态下励磁控制模型,证明了滑模控制策略对包括运行状态切换在内的系统不确定因素具有匹配性,提出了一种基于指数趋近率的双馈风力发电机积分滑模励磁控制策略,并对理想情况、电机参数摄动、电网电压扰动及状态切换情况下双馈风力发电系统空载运行励磁控制进行仿真研究。结果表明,积分滑模励磁控制策略无需任何调整即可实现双馈风力发电机从空载运行到发电运行,且对电机参数摄动及电网电压扰动具有较强的鲁棒性。同时,本文针对粒子群算法在处理双馈风力发电机优化设计等非线性多峰值优化问题时收敛速度慢、易陷入局部最优等问题,提出了混合粒子群优化算法,在惯性权重更新机制中引入了个体模糊调节策略,对同一代的不同粒子根据适应度值优劣模糊选择不同的惯性权重;在粒子位置更新机制中引入了自适应变异操作,根据种群多样性状况自适应确定变异概率和变异因子。Benchmark函数测试结果表明,混合粒子群优化算法动态平衡了全局搜索与局部搜索能力,实现了算法收敛性和种群多样性的同时兼顾,从而提高了收敛速度和寻优精度,不易陷入局部最优,对于非线性多峰值优化问题不失为一种有效地求解方法。此外,本文研究了双馈风力发电机电磁设计特点,探讨了发电机与励磁变换器参数匹配问题,分析了非正弦励磁谐波影响,进而建立了电机优化设计模型。在此基础上,利用混合粒子群优化算法分别实现了双馈风力发电机有效材料成本、额定效率和效率曲线平坦性优化设计,提出了一种基于Pareto最优的双馈风力发电机混合粒子群多目标优化设计方法。优化结果表明,对于双馈风力发电机优化设计问题,混合粒子群优化算法表现出较强的适用性,收敛速度较快,寻优精度较高,有助于实现电机经济技术性能综合最佳化。更多还原

【Abstract】 Doubly fed induction generator (DFIG) with the rotor excitation has been one of the main wind turbine types for the variable speed constant frequency wind power system. It has advantages of excellent speed adjustment, flexible power control ability as well as fractionally rated converter due to the independent control of the excitation current frequency, amplitude and phase angle. Effective excitation current control plays a key role for the DFIG-based wind power system to achieve advantaged operation performance. The researches on the DFIG excitation current control and optimization design are very important to the development of wind power technology and industry, as the DFIG operation characteristics are the prerequisite for the effective excitation control.Focusing on the problem that the DFIG excitation current control tends to be disturbed by system uncertainties, mathematical models of the DFIG excitation current control in no-load stage and power generation stage are built. The sliding mode control strategy is proved to be matched with the uncertainties of the system, such as operating switch. A novel integral sliding mode controller with exponential reaching law for DFIG current control is proposed. Then, the excitation control for DFIG-based wind power system in no-load stage is studied by digital simulation. The simulation is conducted in the cases of ideal grid voltage, fluctuant grid voltage, perturbation of the generator parameters and operating stage switch. The results show that the system under integral sliding mode control accomplishes switches from no-load to generation stages without additional changes in controller, and it is relatively robust to grid voltage disturbance and generator parameter perturbations.The particle swarm optimization (PSO) algorithm has some problems such as slow convergence and high probability of being trapped in local optima when it is applied to the DFIG optimization design and other nonlinear multimodal optimization problem. In this paper, a hybrid particle swarm optimization (HPSO) algorithm, in which a fitness-guided individual fuzzy inertia weight and a diversity-guided adaptive mutation are introduced, is proposed to solve the problems. Different inertia weights should be fuzzily assigned to different particles in the same generation, and the mutation probability and factor are adaptively calculated by the population diversity. The optimization results of benchmark function show that the proposed HPSO algorithm achieves an optimized trade off between the convergence and population diversity, with proper dynamic balance between global and local searching ability. In addition, it also makes improvements in terms of quick convergence, high precision and other commendable optimizing performances such as the absence of premature convergence. Those characteristics make the proposed HPSO algorithm applicable to the nonlinear optimization problems.In addition, an HPSO algorithm integrated with Pareto optimality is proposed for multiobjective optimization design of the DFIG in this paper. The electromagnetic design features are studied, the parameters matching rules between the generator and its excitation converter are discussed, the effects of the harmonics caused by non-sinusoidal excitation currents are analyzed, and an optimization model of the DFIG design is built. Based on the model, the effective material cost, efficiency and flat efficiency curve are separately selected as the optimization goal for the DFIG optimization design by the HPSO algorithm. The optimization results of a DFIG design example show that the proposed HPSO algorithm behaves quick convergence and high precision as it is applied to the benchmark functions optimization. The work of this paper is useful to achieve the overall optimization of the economic and technical performances indices for DFIGs.更多还原