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Post-fault electric power system transient stability prediction method

A power system, transient stability technology, applied in the field of power system, to achieve the effect of improving prediction accuracy, high classification accuracy, and reducing the amount of calculation

Pending Publication Date: 2021-06-11
SHANDONG UNIV OF SCI & TECH
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Problems solved by technology

[0007] The invention provides a power system transient stability prediction method after a fault to solve the problem of the accuracy of the power system transient stability prediction after a fault

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  • Post-fault electric power system transient stability prediction method
  • Post-fault electric power system transient stability prediction method
  • Post-fault electric power system transient stability prediction method

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Embodiment Construction

[0022] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings, in which several embodiments of the present invention are shown, but the present invention can be realized in different forms, and is not limited to the text described On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0023] The post-fault power system transient stability prediction method proposed by the present invention first calculates the correlation between the features based on the Pearson correlation coefficient, and screens out the features with high correlation; then applies the Relief algorithm to the feature importance from large to small Sorting; finally, among the screened out highly relevant features, retain the one with the greatest importance; in order to solve the problem of the accuracy of power system transien...

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Abstract

The invention provides a post-fault electric power system transient stability prediction method, which comprises the following steps of: 1, on the basis of considering power generator terminal voltage fluctuation, acquiring a feature data set through a time domain simulation method so as to analyze the influence of the power generator terminal voltage fluctuation on electric power system transient stability evaluation accuracy; 2, performing feature selection on the feature data set, and performing dimension reduction processing on an original data set by applying a Pearson correlation coefficient and combining a Relief algorithm so as to quickly screen out a better feature subset; and 3, defining an uncertain sample based on a distance value between a sample and an SVM classification hyperplane so as to reduce the calculation amount. According to the invention, the uncertain samples are screened out and are analyzed by using the feature data at the subsequent sampling moment after the fault is removed, so that the number of the uncertain samples can be gradually reduced, and the prediction accuracy of the classifier is improved.

Description

technical field [0001] The invention mainly relates to the technical field of electric power systems, in particular to a method for predicting transient stability of electric power systems after faults. Background technique [0002] In today's society, large-scale grid interconnection, grid-connected operation of clean energy, and increase in load diversity pose new challenges to the safe and stable operation of the power system. As an indispensable energy source, electric energy plays an important role in the development of the national economy and social stability. Large-scale power outages will cause huge economic losses and serious social impacts. In order to deal with the potential threats faced by the power system and avoid large-scale blackouts, it is necessary to pay more attention to the safety and stability of the power system. According to the statistics of power grid instability accidents at home and abroad, the accident rate of transient instability ranks first...

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Application Information

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IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 张桂林关鸾鸾张婧盖文东
Owner SHANDONG UNIV OF SCI & TECH
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