Adaptive Fundamental Component Extraction and Frequency Tracking Algorithm for Power Systems
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摘要: 传统的电网频率跟踪算法一般依赖于调整所选电网模型的响应速度或精度来增强电力系统异常情况下的稳定性,为减小电网谐波或噪声对频率测量的影响,提出了一种自适应基波提取与频率跟踪算法。该算法通过对电网状态的预估,获得电网频率与电压幅值的估计值,用于实时更新无限冲击响应滤波器系数,实现电网的自适应基波提取,同时还给出了滤波器在系数切换时快速稳定的方法,在此基础上,引入鲁棒扩展卡尔曼滤波算法,实现对基波频率的精确跟踪。仿真和实测结果表明,该算法响应速度快,测量精度高,可有效抑制电网噪声对频率跟踪结果的影响,且算法复杂度较低,可以满足电力系统实时应用的要求。Abstract: The conventional frequency tracking algorithm for power systems generally relies on adjusting the response speed or accuracy of the chosen power system model for applications to enhance the stability of power system under abnormal states.To reduce the impacts of harmonic and noise on frequency measurements,an adaptive fundamental component extraction and frequency tracking algorithm was presented.By pre-estimating the state of power grid,this algorithm obtained the estimated frequency and amplitude of voltage,which were used to update infinite impulse response filter coefficients in real time,thus adaptive fundamental wave extraction was achieved.In addition,a method to rapidly stabilize the performance of the fundamental wave filter when filter’s coefficients were switched was proposed.On the base of this,a robust extended Kalman filter was introduced to achieve accurate frequency tracking.Simulation and experimental results show that the new algorithm increases the speed and accuracy of response,effectively suppresses the impacts of noise on the frequency tracking results,significantly lowers the arithmetic complexity over the conventional method and satisfies the requirements of real time applications for power system.
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