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Data-driven transient power angle stability estimation method

A transient stability, data-driven technology, applied in the direction of AC network circuits, electrical components, circuit devices, etc., can solve the problems of lack of theoretical support for the algorithm, affecting the effectiveness of the algorithm, and long judgment time for transient stability

Active Publication Date: 2018-09-14
SHANDONG UNIV +1
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Problems solved by technology

However, the algorithm in this paper lacks the necessary theoretical support, and does not endow the criterion with clear physical meaning from the dynamic development mechanism of the nonlinear dynamic system, and from the perspective of evaluation effect, it takes a long time to judge the transient stability, which affects the The utility of algorithms in practice

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  • Data-driven transient power angle stability estimation method
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  • Data-driven transient power angle stability estimation method

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Embodiment Construction

[0061] The present invention is described in detail below in conjunction with accompanying drawing:

[0062] Starting from the definition of the maximum Lyapunov exponent (MLE) of a dynamic system and its stability analysis mechanism, the present invention proposes a purely data-driven online estimation method for transient power angle stability that does not depend on a physical model of the system. Based on the theory of state space reconstruction, the method decomposes the transient power angle stability analysis problem of the power system into the MLE trajectory analysis problem of the most seriously disturbed units on the relative power angle curve of the system; then, using the recursive least squares algorithm, the classic The MLE calculation method is improved; furthermore, the parameter optimization method for the transient power angle stability problem in the power system is given in the MLE calculation; finally, combined with the MLE trajectory, the judgment basis f...

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Abstract

The invention discloses a model-free transient stability situation estimation method based on data drive. The method comprises: based on the state space reconstruction theory, decomposing a transient power angle stability analysis problem of a power system into an MLE (Maximum Likelihood Estimation) trajectory analysis problem of the most seriously distributed unit on the relative power angle curve of the system; then, improving the classical MLE calculation method by using a recursive least square algorithm; further giving a parameter optimization method for the transient power angle stability problem of the power system in MLE calculation; and finally, giving a judgment basis for transient power angle stability in combination with the MLE curve of the seriously distributed unit on the system, thereby realizing online estimation of transient power angle stability situation. The method for online calculation directly using measurement information has high engineering application value.

Description

technical field [0001] The invention relates to the field of real-time monitoring and early warning of a power system based on a wide area measurement system (WAMS), in particular to a data-driven transient power angle stability estimation method. Background technique [0002] Power system transient stability assessment is the basis for ensuring the safe and stable operation of the power system. In recent years, large-scale power outages have occurred many times in power systems around the world, causing huge losses and serious impacts. One of the main reasons for major blackouts is the lack of effective stable situation monitoring methods and adaptive control strategies after faults or disturbances. At the same time, with the increasing scale of distributed energy grid connection and the wide application of power electronic components, the operating conditions of the power grid are more complicated. The traditional prevention and control mode based on modeling simulation ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H02J3/00
CPCH02J3/00
Inventor 杨明魏少攀韩学山马世英刘道伟
Owner SHANDONG UNIV
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