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ELM and TF based power grid transient stability quick evaluation method

A technology for transient stability and transient stability evaluation of power grids, which is applied in the direction of instruments, data processing applications, and predictions, can solve problems affecting the implementation effect of prediction methods, delays, and lack of actual measurement information, so as to achieve prediction accuracy, Effects of improving reliability and preventing expansion of accident effects

Active Publication Date: 2018-05-18
SOUTHEAST UNIV
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Problems solved by technology

At the same time, the actual measurement information required by the prediction method also has the risk of missing or delaying, but few researchers have considered this, which affects the implementation effect of the prediction method in practical applications

Method used

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  • ELM and TF based power grid transient stability quick evaluation method
  • ELM and TF based power grid transient stability quick evaluation method
  • ELM and TF based power grid transient stability quick evaluation method

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Embodiment Construction

[0020] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0021] figure 1 A framework diagram for the implementation of the ELM and TF-based transient stability rapid assessment method proposed by the present invention. Such as figure 1 As shown, in the specific implementation process, the TF method predicts by collecting the generator power angle trajectory, the ELM method uses the global system information to quickly evaluate the transient stability of the power grid, and the TF method will selectively correct the evaluation results of the ELM method To ensure the accuracy of transient stability assessment, the establishment of TF method and ELM method is based on historical or simulation data. In practical applications, the trajectory model library of the TF method and the transient stability evaluation model of the ELM method will be updated online. When a communication failure occurs in the p...

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Abstract

The invention discloses an ELM (Extreme Learning Machine) and TF (Track Fitting) based power grid transient stability quick evaluation method and belongs to the field of power system transient stability predication. The core of the method is an ELM based transient stability evaluation model and the TF method is utilized for checking and modification, so that improvement of transient stability predication accuracy is realized. At the same time, the method takes into account influence of a power grid communication state and provides solutions for communication interruption, abnormity and the like, so that the reliability of the method in practical application is ensured. The method can be used for quick evaluation of power grid transient stability after severe failure and can provide a decision basis for power grid operation control.

Description

technical field [0001] The invention relates to a method for analyzing the safety and stability of a power grid, in particular to a method for quickly evaluating the transient stability of a power grid based on an extreme learning machine and trajectory matching. Background technique [0002] With the increase of the scale of the power system in terms of geographical distance and load level, and the grid connection and operation of new power electronic equipment, the dynamic characteristics of the power system, such as coherence, instability modes and critical sections, are becoming more and more complex. Operational control becomes more difficult. At the same time, the improvement of power system informatization and data analysis technology supports the development of power system online analysis and prediction technology, which can improve the power system's ability to resist the risk of large-scale blackouts and cascading failures. Therefore, it is of great practical sig...

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Application Information

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IPC IPC(8): G06Q10/06G06Q10/04G06Q50/06
CPCG06Q10/04G06Q10/0639G06Q50/06
Inventor 李峰王琦汤奕
Owner SOUTHEAST UNIV
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