Electric power system transient stability assessment method and device

A transient stability assessment and transient stability technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as the inability to accurately characterize the dynamic process properties of the power system and the inability to account for correlations. To achieve the effect of accurate search, accurate distance and accurate calculation

Inactive Publication Date: 2018-09-28
TSINGHUA UNIV +3
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Problems solved by technology

However, since the dynamic data has been processed and screened before classification or clustering, there may be a certain correlation between the attributes of the samples
If ...

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  • Electric power system transient stability assessment method and device
  • Electric power system transient stability assessment method and device
  • Electric power system transient stability assessment method and device

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Embodiment Construction

[0019] The specific implementation manners of the embodiments of the present invention will be further described in detail below in conjunction with the drawings and embodiments. The following examples are used to illustrate the embodiments of the present invention, but are not intended to limit the scope of the embodiments of the present invention.

[0020] The transient stability assessment of power system based on machine learning can include the following steps: selection of input data and feature extraction, selection of classification algorithm, analysis of classification results and corresponding improvements. The transient stability assessment of power systems based on machine learning mainly uses the principle of "offline training, online simulation". Among them, in the classification algorithm, it is often necessary to calculate various distances and classify them according to the distances, such as KNN nearest neighbor distance, Kmeans distance and distance calculat...

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Abstract

Embodiments of the invention provide an electric power system transient stability assessment method and device. The method comprises the following steps of: obtaining a feature vector of a to-be-assessed point of an electric power system according to a pre-screened key state variable; respectively calculating a mahalanobis distance between the feature vector of the to-be-assessed point and a feature vector of each sample point in a sample set, and searching sample points adjacent to the to-be-assessed point according to the mahalanobis distances; and obtaining an assessment result of the to-be-assessed point according to a classification decision rule and the adjacent sample points. According to the method and device, the mahalanobis distances between the feature vector of the to-be-assessed point and the feature vectors of the sample points are calculated, and the mahalanobis distances sufficiently consider the relevancy between key state variables in the feature vectors, so that thedistance calculation is more correct, the adjacent sample points of the to-be-assessed points can be correctly searched, and the correctness of the assessment result is further improved.

Description

technical field [0001] Embodiments of the present invention relate to the field of power systems, and more specifically, to a method and device for evaluating transient stability of a power system. Background technique [0002] With the access of various new energy sources and the adoption of UHV transmission lines, the power grid has become more complex. Through the detailed modeling of the system, the method of analyzing the power system by using the traditional numerical calculation simulation method has the characteristics of complex model and slow speed. The accumulation of power grid operation data and the adoption of big data methods have brought new ideas to the method of predicting the transient stability of power systems based on data and machine learning, which can speed up the speed of power system simulation. However, if the prediction method based on machine learning directly analyzes the dynamic data of all variables in the power grid, it is not only difficul...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 陈颖凡航黄少伟沈沉梅生伟周二专冯东豪史东宇严剑锋张磊
Owner TSINGHUA UNIV
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