| 引用本文: | 马燕峰,刘伟东,赵书强,范振亚.基于递推随机子空间的电力系统低频振荡辨识[J].电力自动化设备,2016,36(12): |
| MA Yanfeng,LIU Weidong,ZHAO Shuqiang,FAN Zhenya.Low-frequency oscillation identification based on recursive stochastic subspace for power system[J].Electric Power Automation Equipment,2016,36(12): |
|
| 摘要: |
| 为实时提取低频振荡模式信息，采用基于随机子空间的低频振荡递推辨识方法。引入基于双边迭代的子空间递推方法实现随机子空间递推辨识，以提高辨识快速性和灵活性。利用递推误差并结合低频振荡数据的特点，提出一种能够保证快速平稳递推的遗忘因子和加权因子选择策略。对理想数据、仿真数据和WAMS数据分别采用所提方法进行分析，验证了该方法的可行性。 |
| 关键词: 电力系统 随机子空间 低频振荡辨识 子空间追踪 |
| DOI：10.16081/j.issn.1006-6047.2016.12.007 |
| 分类号: |
| 基金项目:中央高校基本科研业务费专项资金资助项目(2016MS-86 )；国家电网公司大电网重大专项资助项目(SGCC-MPLG019-2012) |
|
| Low-frequency oscillation identification based on recursive stochastic subspace for power system |
|
MA Yanfeng1, LIU Weidong2, ZHAO Shuqiang1, FAN Zhenya3
|
|
1.Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China;2.State Grid Tianjin Electric Power Company, Tianjin 300072, China;3.Chifeng Power Supply Company of State Grid Eastern Inner Mongolia Electric Power Co.,Ltd.,Chifeng 024000, China
|
| Abstract: |
| A method of RSSI(Recursive Stochastic Subspace Identification) is proposed to extract the information of low-frequency oscillation mode in real time. The sub-space recursive method based on bi-iteration is introduced to realize the RSSI with enhanced identification speed and flexibility. According to the characteristics of low-frequency oscillation data, a strategy based on the recursive error is proposed for selecting the forgetting factor and weighting factor, which ensures the fast and stable recursion. The applications of the proposed method to the ideal data, simulative data and WAMS data are analyzed, verifying its feasibility. |
| Key words: electric power systems stochastic subspace low-frequency oscillation identification subspace tracking |
