Modeling method for power system transient state stability assessment

Abstract

The invention provides a modeling method for power system transient state stability assessment. The method includes the following steps that power generator track information and a transient state calculation result are collected; a feature value of a power generator is calculated; an initial mathematic model X and a transient state stability assessment mathematic model F are formed; dimensionality reduction is conducted on the transient state stability assessment mathematic model F to obtain a two-dimensional standard mathematic model D. Multidimensional counting is conducted on power generator track curves, a statistic curve can reflect main mean values, change ranges and change rate features of each track curve, statistic features are irrelevant to the scale of a system, the dimensionality curse problem caused by increasing of an analysis system in the data modeling process can be effectively avoided, and meanwhile adverse of power generator information loss on calculation can be reduced to the largest extent.

Description

technical field [0001] The invention relates to a modeling method, in particular to a modeling method for power system transient stability evaluation. Background technique [0002] The transient stability assessment based on machine learning treats the transient stability assessment problem as a two-mode classification problem, that is, the operating state of the system is divided into two categories: stable and unstable; by selecting a set of appropriate features to describe the system State, sample the characteristic data samples of the power system under different operating conditions, and establish a high-dimensional input space; then, use an appropriate classification method to classify the samples, and its mathematical model is as follows figure 1 . [0003] In transient stability assessment, it is very difficult to construct a mathematical model for assessment and select input characteristic variables that are universally applicable and can fully describe the dynamic...

AI Technical Summary

Problems solved by technology

The existing research work is limited to the above-mentioned traditional two-dimensional modeling ideas. When determining the input characteristic variables, most of the operating status at a specific time (such as the time of fault occurrence and the time of fault removal) is considered, and a large number of dynamic characteristics of the intermediate process evolve The information was not applied, which greatly affected the reliability of the final assessment results

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