Extreme event prediction method, device, equipment and storage medium

Abstract

The present application relates to an extreme event prediction method, device, computer equipment, storage medium and computer program product. The method includes: obtaining historical electrical parameters of the power system in a first historical period; obtaining Gibbs measures of historical electrical parameters; inputting the Gibbs measures into a pre-trained event prediction model to obtain the output of the event prediction model Prediction information, the prediction information is used to indicate whether extreme events will occur in the power system at the target future moment after the first historical period; wherein, the event prediction model includes multiple neural network layers constructed based on the XGBoost algorithm and an extension for linking the neural network layers convolutional network. Using this method can realize the prediction of extreme events.

Description

technical field

[0001] The present application relates to the field of power system technology, and in particular to an extreme event prediction method, device, computer equipment, storage medium and computer program product. Background technique

[0002] During the operation of the power system, extreme events such as short circuit of the power system and abnormal oscillation amplitude in the power system will occur. Once the above extreme events occur, they will affect the operation of the power system.

[0003] Therefore, there is an urgent need for a method to predict the occurrence of extreme events. Contents of the invention

[0004] Based on this, it is necessary to provide an extreme event prediction method, device, computer equipment, computer readable storage medium and computer program product capable of predicting the occurrence of extreme events in order to address the above technical problems.

[0005] In the first aspect, the present application provides a...

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