基于共轭梯度分解算法的电网谐波估计  

Power System Harmonics Estimation Based on Conjugate Gradient Decomposition Algorithm

作　　者：蒲小丽[1] 王丽平[1] 

机构地区：[1]南京航空航天大学理学院,江苏南京210016

出　　处：《计算机技术与发展》2013年第2期202-206,共5页Computer Technology and Development

基　　金：国家自然科学基金青年项目(11001128)

摘　　要：快速准确地对电网信号的谐波进行检测与估计,对提高现代电力系统的工作效率有重要意义。传统的快速傅立叶变换(FFT)方法速度较快,但精度不高。近年来,很多学者将谐波估计归结为一个线性极小二乘问题,并用奇异值分解(SVD)算法求解。这类方法虽然提高了精度,但奇异值分解的计算量较大,尤其大规模问题,不能达到"即时"的要求。文中基于共轭梯度分解(CGD)方法对电网中的信号进行谐波估计,不仅降低了SVD算法的计算量,同时提高了FFT的精度,并能应用到严重畸变的定期信号的估计上。初步实验结果验证了该方法的有效性。It is significant to detect and estimate the harmonics of signal for improving the efficiency of the power system quickly and ac- curately. The traditional FFT method is fast, but the precision is not good. Recently, many new methods are proposed, which results in a linear least square problem, which is solved by singular value decomposition （SVD） algorithm. This kind of method improves the preci- sion, but when dealing with the large scale problems, it can not achieve the ＂instant＂ requirement because of the large amount of calcula- tion of singular value decomposition. Ill this paper,use the conjugate gradient decomposition （CGD） algorithm to estimate the harmonics of signals in power system,it not only reduces the computation of SVD algorithm, but also improves_ the precision of FFT, and can be ap- plied to the serious distortion of periodic signal estimation. The numerical simulation results indicate that the algorithm is effective.

关 键 词：奇异值分解 共轭梯度分解 快速傅立叶变换 谐波估计 线性极小二乘方法 

分 类 号：TM711[电气工程—电力系统及自动化]