基于傅立叶基函数神经网络算法的电力系统间谐波分析方法

Inter-harmonic analysis approach in power system using neural network algorithm with Fourier basis functions

间谐波是非整数倍基波频率的谐波信号。间谐波除了具有一般谐波信号的特性外,还会影响谐波补偿装置,因此准确检测间谐波的参数对于电力系统具有十分重要的意义。提出了一种基于傅立叶基函数神经网络算法的电力系统谐波分析方法,研究了该谐波分析方法的收敛性。为了验证该算法的有效性,给出了利用该算法进行间谐波分析的仿真实例。仿真结果表明,文中提出的间谐波分析方法具有计算精度高、训练速度快的特点,因此在电力系统间谐波分析中具有较大的应用价值。

Inter-harmonic is a kind of the harmonic which is not an integer of the fundamental frequency component.The inter-harmonic,same as the integer harmonic,has serious impacts on the design of harmonic compensation equipments,so it is important to analyze inter-harmonic accurately.An artificial neural network（ANN） algorithm based on the Fourier basis functions is presented in the paper by which the amplitudes and phase of harmonic and inter-harmonic could be obtained very fast.The convergence property of the algorithm is researched.In order to validate the algorithm’s validity,the simulation examples of inter-harmonic analysis are given.The simulation results show that the proposed inter-harmonic analysis method is very accurate and the training speed is very fast,so it could be applied to power system inter-harmonic measurement.