电力系统自动化2013，Vol.37Issue(7)：31-35,5.DOI:10.7500/AEPS201204246
电力系统模型类噪声闭环辨识方法
An Ambient Data Based Closed-loop Identification Method of Power System
摘要
Abstract
Small fluctuations caused by random changes of loads exist continuously in power grids, which are referred to as ambient signals. Based on wide area measured ambient data, a method for a closed-loop identifying the power system model based on ambient data is proposed. This model can be used to accurately identify the current operating conditions of a power system. It also provides useful information for system analysis and controller design tasks. The feasibility of closed-loop identification of the system model based on the auto regressive moving averaging vector (ARMAV) model is discussed to show that the power system model can be identified from multiple ambient signals. The method is applied in a two-area four-machine system and a 36-bus system. The results validate the correctness of the proposed method. This work is supported by National Natural Science Foundation of China (No. 51207093), Guangdong Provincial Natural Science Foundation of China (No. S2011040000995), Foundation for Distinguished Young Talents in Higher Education of Guangdong, China (No. LYM11108).关键词
广域测量系统/类噪声信号/系统辨识/闭环辨识/多元自回归滑动平均模型Key words
wide area measurement system (WAMS)/ ambient signal/ system identification/ closed-loop identification/ auto regressive moving averaging vector (ARMAV) model引用本文复制引用
吴超..电力系统模型类噪声闭环辨识方法[J].电力系统自动化,2013,37(7):31-35,5.基金项目
国家自然科学基金资助项目(51207093) （51207093）
广东省自然科学基金资助项目(S2011040000995) （S2011040000995）
广东高校优秀青年创新人才培养计划资助项目(LYM11108) （LYM11108）
深圳市科技计划资助项目(JC201105130407A,GJHS20120621154628775) （JC201105130407A,GJHS20120621154628775）
深圳大学基础研究项目(201117). （201117）
