基于RLS算法的有源滤波器自适应基波检测方法

揭示了有源电力滤波器中谐波补偿指令相位的微小变化都将对谐波控制效果产生很大的负面影响，并导致新的谐波产生。而谐波补偿指令相位偏差主要是由谐波检测算法产生。针对电力系统中信号波形的局部周期性，提出和研究了基于递推最小二乘算法（RLS）的自适应谐波能量最小化基波检测算法，给出了均方意义下的收敛性分析结果。研究表明，在电力系统中出现过渡带及基波信号发生时变时，采用FFT算法的估计结果存在较大的相位偏移。RLS谐波检测方案较Kalman滤波器尤其是FFT方法计算量小，适时跟踪性能好，是有源滤波器中补偿指令检测的有效方法。

Adaptive Fundamental Component Detection Approach to Power Harmonic Compensation Based on the RLS Algorithm

The power harmonic control and compensation in active power filters is sensitive to the phase of reference template and a small displacement of the phase may cause large compensation deviations. Considering the nature of local periodicity of current waveform in power system, the recursive least squares (RLS) scheme used to extract the fundamental harmonic on time is proposed and studied. The performances of the fundamental harmonic estimation are discussed in the presence of time-varying harmonic within a transitional band, and the convergence analysis result of the RLS scheme is given also. Experimental results show that both the RLS and Kalman shcemes can trace time-varying harmonic on time within a transitional band with quicker response than FFT method, and the RLS scheme tracks fundamental signal more steadily and with less computational burden than the Kalman filter. The harmonic compensation results using the FFT method are worse than the results associated with RLS scheme due to its harmonic phase detection delay.