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利用相关分析的区间振荡振型快速估计方法 被引量:8

Algorithm for Inter-area Oscillation Mode Shape Estimation Using Correlation Analysis
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摘要 为了提高区间振荡动态特性中振型信息的有效获取速度,提出了一种利用相关分析的快速估计区间振荡振型的新方法。它首先通过一个由先验知识设计并在线校正的低通或带通滤波器,从电力系统广域测量系统(wide area measurement system,WAMS)采集的各联络线有功功率信号中提取以弱阻尼模式为主导的分量信号,然后对该信号进行时域相关性分析,借助自相关和互相关系数确定该模式下各区间功率偏差的归一化幅值和相对相位,进而获得其功率偏差振型,并结合离线计算、在线修正的模态表确认等效转速偏差振型和对应模式。通过对一对弱阻尼的平稳信号和一对非指数时变幅值的反相非平稳信号进行分析,表明了相关分析法的适用性。案例分析在一个4区域9节点系统和一个华东电网规划系统中展开,结果表明了该方法的快速性、有效性以及潜在的实用性。 In order to improve the effective acquisition speed for mode shape information in the dynamic characteristics of inter-area oscillation,we put forward a new algorithm for rapid estimating the inter-area oscillation mode shapes and corresponding modes using correlation analysis.Firstly,the algorithm extracts a weak damping component which is associated with objective mode from each tie-line active power signal,and the signal comes from WAMS through a low-pass or band-pass filter which is designed by a priori modal knowledge obtained from off-line calculation.Then,the self-correlation and cross-correlation coefficients resulted from correlation analysis of these time-domain signals are used to determine an inter-area mode shape of tie-line power deviation and equivalent speed deviation which always corresponds to a mode.Finally,the results about inter-area oscillation features are checked with the modal form from off-line calculation in order to confirm the dominant mode and its mode shape in current state.Two pairs of stationary and non-stationary synthetic signals are utilized to verify the applicability of this method.The case studies have been carried out on a 4-area 9-bus system and a planning case in East China Power Grid.The results show that the proposed algorithm is efficient and effective,indicating the potential practicability for WAMS of bulk power system.
出处 《高电压技术》 EI CAS CSCD 北大核心 2011年第2期436-443,共8页 High Voltage Engineering
基金 国家"十一五"科技支撑计划重大项目(2006BA02A17)~~
关键词 相关分析 区间振荡 转速偏差振型 功率偏差振型 振型估计 模态表 correlation analysis inter-area oscillation mode shape for speed deviation mode shape for power deviation mode estimation modal form
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