张培远,吴璇,吴应华,杨明芳,朱亚东.新型虚拟磁链定向的Hopfield神经网络谐波电流检测[J].电测与仪表,2017,54(11):. zhangpeiyuan,wuxuan,wuyinghua,yangmingfang,zhuyadong.Harmonic Current Detecting Based on Hopfield Neural Network with New Virtual Flux Orientation[J].Electrical Measurement & Instrumentation,2017,54(11):.
新型虚拟磁链定向的Hopfield神经网络谐波电流检测
Harmonic Current Detecting Based on Hopfield Neural Network with New Virtual Flux Orientation
The real time performance and accuracy of harmonic current detection are directly related to the compensation effect of active power filter. Compared to the phase locked loop, virtual flux can obtain more accurate orientation as well as faster response even in the case of the grid voltage fluctuations. In this paper, by using the new algorithm which is consisted of a high-pass filter and transformed coordinate system, we improve the phase error caused by the integrator in the virtual flux algorithm. Using Hopfield neural networks to detect harmonic current ,this method construct the feedback neural network based onSenergy function, through continuous feedback convergence and reached balance in the finally. Simulation results illustrate that, the method of Hopfield neural network with virtual flux orientation can simultaneously detect the grid fundamental and total harmonic as well as the specific number of harmonic currents quickly and accurately. In the situation of load mutation and voltage fluctuation, the detection methods put forward by this paper has excellent real time performance, high accuracy, and more strong robustness compared to the results with ip-iq method.
