Power system transient frequency prediction model updating method based on data inheritance idea

A prediction model and power system technology, applied in genetic models, prediction, calculation models, etc., can solve the problem of low model update efficiency, achieve the effect of improving frequency prediction performance and maintaining stable operation

Inactive Publication Date: 2019-08-27
LIYANG RES INST OF SOUTHEAST UNIV +1
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Problems solved by technology

However, based on the traditional machine learning method to predict the transient frequency of the power system, all the historical data need to be used when the model is updated, resulting in repeated training of a lot of historical data, which makes the model update efficiency inefficient

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  • Power system transient frequency prediction model updating method based on data inheritance idea
  • Power system transient frequency prediction model updating method based on data inheritance idea
  • Power system transient frequency prediction model updating method based on data inheritance idea

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Embodiment Construction

[0053] Such as figure 1 As shown, the embodiment of the present invention provides a power system transient frequency prediction model update method based on the idea of ​​data inheritance, including:

[0054] Step S1: Use the extreme learning machine ELM algorithm to train historical transient fault samples to generate a historical frequency prediction model;

[0055] Step S2: Monitor the operating status of the system in real time to determine whether a transient fault occurs;

[0056] Step S3: If a transient fault occurs in the power system, collect system operation data before and after the fault, and proceed to step S4, otherwise continue to return to step S2;

[0057] Step S4: On the basis of the historical prediction model, the frequency prediction model is updated by using the newly added transient fault samples to obtain a new prediction model.

[0058] In this embodiment, the IEEE39 node with actual topology structure correction is used for analysis, in which the t...

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Abstract

The invention provides a power system transient frequency prediction model updating method based on a data inheritance idea. The method comprises the following steps of firstly, training a historicaltransient fault sample by utilizing an extreme learning machine (ELM) algorithm, and establishing a historical frequency prediction model; and if the power system has a transient fault during the process of monitoring the running state of the system in real time, collecting the system running data before and after the fault, and then updating the historical frequency prediction model according toa newly added transient fault sample. According to the method, the data inheritance thought is applied to the frequency prediction model updating process, the frequency prediction model can be rapidlyupdated in a power system transient frequency prediction scene with few historical samples, the frequency prediction performance is improved, the emergency control measures can be made and adopted intime, and the method has important significance for maintaining the stable operation of a power system.

Description

technical field [0001] The invention relates to the technical field of power system situation awareness and trend prediction, in particular to a power system transient frequency prediction model update method based on the idea of ​​data inheritance. Background technique [0002] With a large number of new energy sources such as photovoltaics and wind power connected to the grid and gradually replacing conventional power sources, the equivalent inertia of the system is gradually reduced, resulting in more serious system transient problems, especially transient frequency safety problems, which is not conducive to the safe and stable operation of the power system. Rapid prediction of power system transient frequency is of great significance for timely taking emergency control measures and improving the safety and stability of power system. [0003] In recent years, artificial intelligence and machine learning have developed rapidly. Machine learning methods can effectively make...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N3/00G06N3/04G06N3/08G06N3/12G06Q50/06
CPCG06Q10/04G06N3/08G06N3/006G06N3/126G06Q50/06G06N3/045
Inventor 汤奕张超明
Owner LIYANG RES INST OF SOUTHEAST UNIV
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