互联电网功率振荡辨识方法应用研究

1)南方电网科学研究院有限责任公司,广州 510080; 2)深圳大学机电与控制学院,深圳 518060; 3)清华大学电机工程与应用电子技术系,北京100084

电气工程; 功率振荡; 互联电网; Prony法; 自回归滑动平均法; 随机子空间法

Applicability analysis of algorithms for electromechanical mode identification based on measured data
Men Kun1, Wu Chao2, Tu Liang1, and Lu Chao3

Men Kun1, Wu Chao2, Tu Liang1, and Lu Chao31)Electric Power Research Institute of China South Power Grid, Guangzhou 510080, P.R.China2)College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, P.R.China3)Department of Electrical Engineering, Tsinghua University, Beijing 100084, P.R.China

electrical engineering; power oscillation; interconnected power grid; Prony method; autoregressive moving average method; stochastic subspace method

DOI: 10.3724/SP.J.1249.2014.03299

备注

为应对中国大规模互联电网的功率振荡问题, 讨论Prony法、 自回归滑动平均法和随机子空间法的应用性. 分别以两区四机系统和EPRI-36节点系统等不同规模的典型仿真系统为例, 将上述方法用于明显扰动系统响应和随机扰动系统响应等典型信号的分析,提取系统振荡特征信息, 比较不同方法的应用性能, 研究存在外部测量干扰时方法的使用效果, 得到各种辨识方法在实际电网中应用性的一般结论.

In response to the power oscillation issue of China's interconnected power grids, the applicability of the Prony method, the autoregressive moving average method and the stochastic subspace method are systematically discussed in this paper. Based on the review of their elementary principles, with the two-area four-machine system and the 36-node benchmark system as examples, these methods are used to estimate the oscillation information from ringdown data and ambient data respectively. Moreover, the influence of external measurement disturbances is also considered. Finally some general conclusions about the applicability of these methods in actual power grids are drawn from the simulation cases.

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