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Power grid disaster assessment method based on deep neural network

A technology of deep neural network and neural network model, which is applied in the field of power grid disaster assessment based on deep neural network, can solve problems such as power grid operation loss, and achieve the effect of solving difficulties and reducing the number of scenarios.

Active Publication Date: 2021-09-17
GUIZHOU POWER GRID CO LTD
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AI Technical Summary

Problems solved by technology

The hidden dangers of the power grid cannot be understood in time and remedial measures can be taken, resulting in immeasurable losses in the operation of the power grid

Method used

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  • Power grid disaster assessment method based on deep neural network
  • Power grid disaster assessment method based on deep neural network
  • Power grid disaster assessment method based on deep neural network

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Embodiment 1

[0051] The calculation effect of the existing scene-based disaster assessment optimization model depends on the size of the number of scenes. In order to fully represent the characteristics of random variables, the number of scenes directly obtained by the scene generation method is usually huge, which will make the specific optimization calculation face. Difficulty solving.

[0052] Therefore, see figure 1 and figure 2 , the present invention provides a power grid disaster assessment method based on a deep neural network, comprising:

[0053] S1: Obtain historical power grid disaster scenario data for statistical analysis;

[0054] It should be noted that the power grid disaster scenario data includes disaster data, rainstorm data, fault data and power grid distribution data.

[0055] S2: Preprocess the disaster scene data, and use the disaster assessment indicators to establish a rating system;

[0056] Specifically, using the obtained historical power grid disaster sce...

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Abstract

The invention discloses a power grid disaster assessment method based on a deep neural network. The method comprises the steps of obtaining historical power grid disaster scene data for statistical analysis; preprocessing the historical power grid disaster situation scene data, and establishing a rating system by using disaster situation evaluation indexes; constructing a neural network model, classifying the disaster situations according to the severity of the disaster situations, and outputting the classified disaster situations as a model; after the preprocessed sample data are loaded to the neural network model, training parameters are selected to train and learn the neural network model; obtaining a new power grid scene in real time, inputting the new power grid scene into the trained neural network model, and obtaining the disaster assessment level in real time, thereby solving the problem that the specific optimization calculation of the existing scene-based disaster assessment optimization model is difficult to solve.

Description

technical field [0001] The invention relates to the technical field of power grid security, in particular to a power grid disaster assessment method based on a deep neural network. Background technique [0002] In recent years, the operating environment of the power grid has become increasingly severe and complex, with strong convective disasters such as rain and snow freezing, storm surges, typhoons, torrential rain and lightning, and extreme weather such as haze, strong winds, sandstorms, and mountain fires (referring to rare meteorological events in history, the probability of occurrence The power grid is increasingly affected by the hidden dangers caused by the failure of power grid facilities and electricity services. The hidden dangers in the power grid cannot be understood in time and remedial measures can be taken, resulting in immeasurable losses in the operation of the power grid. [0003] At present, researchers conduct power grid disaster assessment by establish...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06N3/04G06N3/08
CPCG06Q10/04G06Q50/06G06N3/08G06N3/045Y04S10/50
Inventor 林爽王裴培唐钰翔孙怡长秦萃丽毛健余志强邹勇吴歧李沛
Owner GUIZHOU POWER GRID CO LTD
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