基于改进自适应局部迭代滤波的谐波检测方法研究

针对大量非线性负荷及电力电子设备广泛应用导致的电力系统谐波成份非平稳性和复杂性日益突出,难以识别和检测的问题,在引入自适应局部迭代滤波算法的基础上,提出了基于改进自适应迭代滤波与希尔伯特变换的谐波检测方法。改进自适应迭代滤波算法利用Fokker-Planck方程构建滤波函数,经滤波筛选获取具有平稳特征的本征模态分量,具有坚实的数学基础,且能够有效地避免经验模态分解算法存在的模态混叠问题。首先利用改进自适应迭代滤波算法分解得到周期分量,对各分量进行Hilbert变换,提取包括频率、幅值、相位在内的谐波特征参数。测试信号及实测数据分析结果证明了所用方法的有效性,与经验模态分解的对比结果充分验证了本方法在电力系统谐波检测中的强适应性。

Study on the harmonic detection method based on improved adaptive local iterative filtering

Aiming at the increasingly prominent non stationarity and complexity of harmonic components, which are hard to be identified and detected, caused by the extensive application of a large number of non linear loads and electronic equipment in power system, on the basis of introducing the adaptive local iterative filtering algorithm, this paper proposes a harmonic detection method based on Improved Adaptive Local Iterative Filter (IALIF) and Hilbert transformation. The IALIF algorithm utilizes the Fokker Planck equation to construct filter functions and screen out the intrinsic mode components with stationary features through filtering. This algorithm has solid mathematic basis and can avoid the mode mixing existing in empirical mode decomposition algorithm effectively. In this paper the IALIF algorithm is used to obtain the period components, then Hilbert transformation is performed on these components to extract the harmonic characteristic parameters, such as frequency, amplitude and phase. The analysis results of the test signal and real measured data prove the effectiveness of the proposed method, and the comparison result with empirical mode decomposition fully verifies strong adaptation of the proposed method in electric system harmonic detection.