Robust state estimation method based on piecewise linearity weight factor function

A robust state estimation, piecewise linear technology, applied in the field of power system, can solve problems such as lack of engineering application and lack of calculation methods

Inactive Publication Date: 2013-10-02
STATE GRID CORP OF CHINA +1
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Problems solved by technology

These newly researched error-resistant state estimation methods still lack a large number of engineering application examples, and there is still a lack of a set of practical and reliable calculation methods in the engineering practice of state estimation against gross errors in measurement systems

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  • Robust state estimation method based on piecewise linearity weight factor function
  • Robust state estimation method based on piecewise linearity weight factor function
  • Robust state estimation method based on piecewise linearity weight factor function

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Embodiment Construction

[0060] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0061] A robust state estimation method based on the piecewise linear weight factor function proposed in this embodiment, in the iterative process of solving the state estimation model, calculates the variable weight factor of the measurement according to the weight factor function and corrects the measurement weight, and the residual For the quantity measurement with a large difference in absolute value, by weighting it, its influence on the subsequent iterative process is gradually reduced and weakened, so that a more accurate state estimation result can be finally obtained. Finally, the weight of the measurement that makes the absolute value of the residual is large will be reduced, so that the influence in the next iteration will also be reduced, and so on until convergence.

[0062] Specifically, the flow chart of t...

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Abstract

The invention provides a robust state estimation method based on a piecewise linearity weight factor function and belongs to the technical field of power system computation. The method includes the steps of step 1, establishing a robust state estimation model based on the weight factor function, step 2, selecting and measuring a weight factor function equation and determining and measuring equivalent weight factors, and step 3, solving the variable weight factor robust state estimation model, and obtaining and outputting estimation results. Aiming at section difference of traditional weight least square estimation on bad data identification, the robust state estimation method based on the piecewise linearity weight factor function is proposed, a weight least square estimation method and the robust estimation principle are combined, therefore, computation efficiency and quickness of the weight least square estimation are reserved, and also the state estimation algorithm has high robust performance.

Description

technical field [0001] The invention belongs to the field of power systems, and in particular relates to a robust state estimation method based on a piecewise linear weight factor function. Background technique [0002] In the power grid dispatching system, due to various interferences in the transmission of substation telecontrol information, the measurement data obtained by the SCADA system of the dispatching center contains measurement noise, and even produces bad data. The traditional least squares state estimation is the most widely used at present. It has a simple model, a small amount of calculation, and has excellent properties such as optimal consistency and unbiased estimation for the quantity measurement under the ideal normal distribution condition. However, since the actual measurement does not necessarily completely obey the normal distribution, it is difficult to completely detect and identify bad data, and the statistical characteristics of the measurement er...

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Application Information

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IPC IPC(8): G06F19/00
Inventor 刘俊石飞姚建国杨胜春杨争林於益军冯树海王礼文李峰王勇汤必强郭晓蕊徐鹏潘玲玲
Owner STATE GRID CORP OF CHINA
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