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Measurement-Based Transmission Line Parameter Estimation with Adaptive Data Selection Scheme

机译:基于自适应数据选择方案的测量传输线参数估计

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摘要

Accurate parameters of transmission lines are critical for power system operation and control decision making. Transmission line parameter estimation based on measured data is an effective way to enhance the validity of the parameters. This paper proposes a multi-point transmission line parameter estimation model with an adaptive data selection scheme based on measured data. Data selection scheme, defined with time window and number of data points, is introduced in the estimation model as additional variables to optimize. The data selection scheme is adaptively adjusted to minimize the relative standard deviation (RSD) of estimated parameters. An iterative technique derived from the Newton method is adopted to solve the proposed model by fitting the relationship between the RSD and data selection scheme with exponential functions. Simulated data are applied to illustrate the performance of the proposed model. Some 500kV transmission lines from a provincial power system of China areestimated to demonstrate the applicability of the presented model. The superiority of the proposed model over fixed data selection schemes is also verified.
机译:传输线的准确参数对于电力系统的运行和控制决策至关重要。基于实测数据的传输线参数估计是提高参数有效性的有效途径。提出了一种基于实测数据的自适应数据选择方案的多点传输线参数估计模型。在估计模型中引入了由时间窗口和数据点数定义的数据选择方案,作为要优化的其他变量。自适应地调整数据选择方案,以使估计参数的相对标准偏差(RSD)最小化。采用牛顿法的迭代技术,通过用指数函数拟合RSD和数据选择方案之间的关系来求解所提出的模型。仿真数据用于说明所提出模型的性能。估算了中国某省级电力系统的约500kV输电线路,以证明该模型的适用性。相对于固定数据选择方案,该模型的优越性也得到了验证。

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