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The theory and algorithm of detecting and identifying measurement biases in power system state estimation

机译:电力系统状态估计中检测和识别测量偏差的理论与算法

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The theory and algorithm of the detection and identification of measurement biases are developed. A fast and efficient recursive measurement biases estimation identification method is proposed. A set of linearized recursive formulae are developed to recursively calculate measurement residual averages and their variance. Using this algorithm, the long list of suspicious data can be avoided and the computational speed can be increased greatly. This adds a new function of monitoring on the operation of measurement system to the real network state analysis application software in power system control center and can improve the quality of the state estimation and the ability to detect and identify the bad data.
机译:开发了测量偏差检测和识别理论和算法。 提出了一种快速高效的递归测量偏置估计识别方法。 开发了一组线性化递归公式以递归地计算测量残余平均值及其方差。 使用该算法,可以避免可疑数据的长目表,并且可以大大增加计算速度。 这增加了对电力系统控制中心的实际网络状态分析应用软件进行测量系统的操作的新功能,可以提高状态估计的质量和检测和识别不良数据的能力。

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