引用本文:颜 伟,赵雪骞,陈 俊,李世明.电网设备错误参数的支路量测标幺值残差代数和均值辨识法[J].电力自动化设备,2013,33(2):
YAN Wei,ZHAO Xueqian,CHEN Jun,LI Shiming.Grid equipment parameter error identification based on mean algebraic sum of branch measurement normalized residuals[J].Electric Power Automation Equipment,2013,33(2):
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电网设备错误参数的支路量测标幺值残差代数和均值辨识法
颜 伟, 赵雪骞, 陈 俊, 李世明
重庆大学 输配电装备及系统安全与新技术国家重点实验室,重庆 400030
摘要:
充分考虑随机量测误差的正态分布特点,提出了基于单一设备多时段相量测量单元(PMU)或数据采集与监视控制(SCADA)量测的错误参数均值辨识法。该方法首先基于线路、双绕组和三绕组变压器的等值电路模型及其PMU或SCADA量测信息,提出单一设备同一时段的综合标幺值残差指标,以综合反映量测与参数误差对残差的影响;然后以方差系数为收敛条件,求取多时段综合残差代数和均值的绝对值(指标T),以突出参数误差对综合残差均值的影响;最后根据综合残差均值的大小来辨识设备的参数错误。分析了文献错误参数综合残差平方和均值辨识法存在的问题,论证了所提方法在消除量测误差影响和确定均值样本数两方面的优势,并通过仿真分析验证了所提方法的有效性。
关键词:  参数辨识  标幺值  残差  相量测量单元  数据采集与监视控制
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Grid equipment parameter error identification based on mean algebraic sum of branch measurement normalized residuals
YAN Wei, ZHAO Xueqian, CHEN Jun, LI Shiming
State Key Laboratory of Power Transmission Equipment & System Security and New Technology, Chongqing University,Chongqing 400030,China
Abstract:
According to the normal distribution of random measurement error,a method of parameter error identification is applied for grid equipment,which is based on the mean values of its PMU or SCADA measurements for multiple periods. Based on the equivalent circuit model of transmission line,double-winding transformer and three-winding transformer,and together with their PMU or SCADA measurements,a comprehensive normalized value residual index of single equipment for the same period is presented,which comprehensively reflects the influence of both measurement error and parameter error on the residuals. With the variance coefficient as the convergence condition,the absolute mean value of the algebraic sum of comprehensive residuals for multiple periods (index T ) is obtained,which mainly reflects the influence of parameter error on the residuals. According to index T,the parameter error of the device is identified. The identification method based on the mean square sum of comprehensive residuals presented in the reference is analyzed and the advantages of the proposed method in the elimination of measurement error influence and the determination of sample size are introduced. Its effectiveness is verified by simulative analysis.
Key words:  parameter identification  normalized value  residual  PMU  SCADA

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