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Design and optimization of control parameters based on direct-drive permanent magnet synchronous generator for wind power system

机译:基于直驱永磁同步发电机的风力发电系统控制参数的设计与优化

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The direct-drive permanent magnet synchronous generator (DDPMSG) for wind power system uses a back-to-back double PWM converter. PI controller based on decoupling control strategies is used to control generator side converter and grid side converter. But the parameters of the PI controller are difficult to obtain correctly. Though manual tuning method is applied to regulate the parameters, the method would waste a lot of time and greatly depend on the experience. The paper analyses the mathematical model of direct-drive permanent magnet synchronous wind power generation system. It presents a particle swarm optimization (PSO) method for determining the parameters of PI controller for PMSG to improve the control ability. PSO is powerful stochastic evolutionary algorithm that is used to find the global optimum solution in search space. Under the condition of wind speed mutation, the simulation results of PMSG system after PI parameter optimization show that the PI control with PSO algorithm can fit the real value. The PSO controller has fast convergence rate, strong adaptability and good dynamic performance.
机译:风力发电系统的直接驱动永磁同步发电机(DDPMSG)使用背靠背双PWM转换器。基于解耦控制策略的PI控制器用于控制发电机侧变流器和电网侧变流器。但是,PI控制器的参数很难正确获取。尽管使用手动调整方法来调节参数,但是该方法会浪费大量时间,并且在很大程度上取决于经验。本文分析了直驱永磁同步风力发电系统的数学模型。提出了一种粒子群算法(PSO),用于确定PMSG的PI控制器参数,以提高控制能力。 PSO是功能强大的随机进化算法,用于在搜索空间中找到全局最优解。在风速突变的条件下,经过PI参数优化的PMSG系统仿真结果表明,采用PSO算法的PI控制可以满足实际值。 PSO控制器收敛速度快,适应性强,动态性能好。

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