小波变换和神经网络在SVC中的应用研究  

Research on Application of Wavelet Transform and ANN in SVC

作　　者：郑常宝[1] 张力[1] 郑长勇[2] 曾野[1] 

机构地区：[1]安徽大学计算智能与信号处理教育部重点实验室,合肥230039 [2]安徽建筑工业学院计算机系,合肥230022

出　　处：《系统仿真学报》2007年第21期5011-5014,共4页Journal of System Simulation

基　　金：安徽省科技厅科技攻关研究项目(06012068B);安徽大学211工程学术创新团队资助

摘　　要：电力系统无功功率平衡非常重要,无功功率补偿能进行基波功率因数校正。提出了一种检测基波无功功率的方法和用神经网络补偿TCR的非线性方法,并用于FC+TCR型SVC中。用小波变换滤除电压和电流中的谐波,保留基波,用基波电压和电流求出基波功率因数。TCR具有非线性特性,ANN具有非线性映射能力,用神经网络补偿TCR的非线性,方法简单实用。对采用基波无功功率因数检测方法和ANN非线性补偿的SVC控制系统的进行了访真,给出了仿真结果。Reactive power balance of power system is important and reactive power compensation can correct displacement power factor. Methods of testing displacement power factor and nonlinear compensation of TCR using ANN were proposed and were used in SVC. Harmonics of voltage and current was filtered using wavelet transform, and displacement power factor was calculated based on fundamental parameter. TCR has nonlinear characteristic, ANN has nonlinear map ability and was employed for nonlinear compensation of TCR. The SVC control system was simulated and the result was provided.

关 键 词：小波变换 神经网络 无功功率补偿 非线性补偿 基波功率因数 

分 类 号：TM761[电气工程—电力系统及自动化]