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Statistical measurement calibration based on state estimator results

机译:基于状态估计器结果的统计测量校准

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An approach to a statistical calibration of active power, reactive power and voltage measurements is shown. Measurement errors are studied according to their nature: systematic, installation and random errors. Effect of installation and systematic measurement errors on an energy management system (EMS) is analysed, paying special attention to its effect in state estimator behaviour. State estimator accuracy is discussed in order to analyse its use as a measurement standard. Statistical calibration is deeply explained: series of measured and estimated data are statistically processed getting valuable information regarding each measurement. This information is further analysed in order to remotely calibrate those measurements with systematic and installation errors, along with the determination of unknown state estimator measurement weights. The paper shows that once measurements have been statistically calibrated, immediate replacement of outdated equipment can be avoided, and furthermore, measurement errors can be dealt with as pure random errors (normally distributed).
机译:显示了对有功功率,无功功率和电压测量值进行统计校准的方法。根据测量误差的性质进行研究:系统误差,安装误差和随机误差。分析了安装和系统测量误差对能源管理系统(EMS)的影响,尤其要注意其在状态估计器行为中的影响。讨论了状态估计器的准确性,以便分析其作为测量标准的用途。统计校准得到了深入的解释:对一系列测量和估计的数据进行统计处理,以获得有关每次测量的有价值的信息。为了对这些测量值进行系统和安装错误的远程校准,以及确定未知的状态估计器测量权重,将对这些信息进行进一步分析。本文表明,一旦对测量结果进行了统计校准,就可以避免立即更换过时的设备,此外,还可以将测量误差视为纯随机误差(正态分布)。

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