基于小波神经网络的风力发电系统暂态电能质量分析

Analysis of Transient Power Quality of Wind Energy Generation System Based on Wavelet Neural Network

结合当前风力发电大规模发展、风电系统大规模并网的趋势,针对风电系统并网所存在的暂态电能质量问题,将广泛运用于信号处理的同神经网络相结合,构造了小波神经网络,详细的分析了小波变换和神经网络的基本原理,给出了小波神经网络的拓扑结构图及风电系统暂态电能质量的仿真。仿真结果表明,小波神经网络可以有效的对暂态故障进行检测、时间定位及预测,和其它控制方式相结合可以改善暂态电能质量。

Combined with the trend of the large scale development of the current wind power and the large-scale grid-connection of the wind energy generation system and aiming at the problems of transient power quality in power systems connected with wind energy generation,this paper constructs a wavelet neural network combined with wavelet transform method,which analyzes the basic principles of wavelet transform and neural network in detail & gives the topology diagram of wavelet neural network and the simulation of transient power quality of wind energy generation system.The results of the simulation indicate that the wavelet neural network can effectively carry up fault detection,time location and forecast of transient fault.The transient power quality can be improved with this wavelet neural network combined with other control method.