基于PSO-GSA算法的含DFIG互联系统AGC优化控制研究

传统双馈感应风力发电机(DFIG)的解耦控制使其无法响应电网的频率变化。随着风电渗透率的不断提高,电网调频压力不断增大,有必要对含DFIG互联系统AGC优化控制进行研究。首先建立了将风电作为"负的负荷"的两区域AGC模型,通过引入改进的虚拟惯性控制使DFIG具有更好的频率响应的能力。同时以快速消除系统区域控制偏差和风机转速偏差为目的,采用PSO-GSA算法对控制区PID控制器和DFIG转速控制单元PI控制器参数进行优化。仿真结果表明,单个区域受负荷扰动时,风电参与调频时能提供更多的有功功率支撑以减小同步机调频出力,能有效缓解同步机调频压力。PSO-GSA算法较PSO和GSA迭代速度快且适应度值更好,基于PSO-GSA参数优化后的控制器对系统区域频率偏差、联络线功率变化和区域控制偏差信号的超调量和调节时间都有明显改善,增强了系统的稳定性。

Research on PSO-GSA algorithm optimization for interconnected AGC system including DFIG wind turbines

The decoupling control of the traditional Doubly-Fed Induction Generator (DFIG) based on wind turbine makes it impossible to respond to the frequency variation of the power system, the pressure of frequency modulation in power system is increasing because of the daily increasing penetration of wind power, as a result, it is of great significance to study the AGC optimal control of two-area interconnected power systems which includes DFIG. Wind power is regarded as a negative load which is incorporated into the two-area interconnected automatic generation control model, DFIG has better capability of frequency response due to the improved virtual inertia control. Moreover, the proposed PSO-GSA algorithm is used to optimize the parameters of PID controller of AGC and PI controller of the speed control block. Simulation results show that frequency regulation of DFIG could effectively relieve frequency deviation and pressure of synchronous machine in the power system. Moreover, PSO-GSA algorithm in this paper has faster convergence speed and better fitness value than PSO and GSA. The controller optimized by PSO-GSA algorithm is able to improve system frequency deviation, tie line power, area control error, overshoot and stabilization time, which enhances the stability of the power system. This work is supported by National Natural Science Foundation of China (No. 51477143).