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Statistical measurement calibration based on state estimator results

机译:基于状态估计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 The paper shows that once measurements have been statistically calibrated, immediate replacement of outdated equipment can be avoided, and furthermore, measurement errors can be dealt with as pure random errors (normally distributed).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:示出了有功功率,无功和电压测量的统计校准的方法。根据其性质研究了测量误差:系统,安装和随机错误。分析了安装和系统测量误差对能量管理系统(EMS)的影响,特别注意其在国家估算机构的作用。讨论了状态估计准确度,以分析其用作测量标准。统计校准深度解释:统计地处理了一系列测量和估计数据,获得了有关每种测量的有价值的信息。进一步分析了该信息以便远程校准具有系统和安装误差的那些测量,以及确定未知状态估计测量权重的确定。纸质表明,一旦测量已经过统计校准,可以避免立即更换过时的设备,此外,可以用纯无随机误差(通常分布)处理测量误差。

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