电力系统保护与控制2012，Vol.40Issue(1)：12-17,49,7.
基于改进的ARMA递推算法的低频振荡模式在线辨识
Improved ARMA recursive algorithm for online identification of low frequency oscillation modes
陈刚 1龚啸 2李军 3古志明4
作者信息
- 1. 南方电网科学研究院,广东广州510080
- 2. 输配电装备及系统安全与新技术国家重点实验室(重庆大学),重庆400044
- 3. 输配电装备及系统安全与新技术国家重点实验室(重庆大学),重庆400044
- 4. 重庆市电力公司,重庆400015
- 折叠
摘要
Abstract
In order to improve the level of real-time monitoring of low frequency oscillation, this paper proposes to use a two parts weighted recursive least square (WRLS) algorithm based on auto-regressive moving-average (ARMA) model to estimate the low frequency oscillation modes, and extracts the domain modes of low frequency oscillation by the method of ARMA spectrum estimation. The improved algorithm uses the obtained white noise estimates by fitting the higher order autoregressive (AR) model by the WRLS method in the conventional WRLS method, and then it has the preferable accuracy and the fast convergence rate of parameter identification. The validity of proposed algorithm is demonstrated with simulation data from New-England 39-bus system. Comparison with proposed algorithm and conventional weighted recursive least square algorithm shows the advantages of the algorithm in this paper. Finally, identification analysis of practical signal measured of PMU in some grid demonstrates that the proposed algorithm can accurately estimate the frequency and damping ratio of power system low frequency oscillation domain modes, so the proposed algorithm has the practical project significance.关键词
自回归滑动平均模型/加权递推最小二乘算法/ARMA谱/低频振荡在线辨识/主导模式Key words
ARMA model/weighted recursive least square method/ARMA spectrum/online identification of low frequency oscillation/domain modes分类
信息技术与安全科学引用本文复制引用
陈刚,龚啸,李军,古志明..基于改进的ARMA递推算法的低频振荡模式在线辨识[J].电力系统保护与控制,2012,40(1):12-17,49,7.
