Power grid fault critical clearing time discrimination method based on improved Softmax regression

A technology of critical cutting time and discrimination method, which is applied in the direction of electrical components, circuit devices, AC network circuits, etc., to achieve the effect of expanding the selection range, improving applicability, and improving the cost function

Active Publication Date: 2018-04-20
STATE GRID LIAONING ELECTRIC POWER RES INST +2
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Problems solved by technology

[0007] In order to solve the problems existing in the existing methods, the present invention proposes a grid fault critical removal time discrimination method based on improved Softmax regression, which can expand the feature selection range and cover the static quantities of all equipment in the online data of the power system. Automatically identify the main features that have the greatest impact on grid stability

Method used

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  • Power grid fault critical clearing time discrimination method based on improved Softmax regression
  • Power grid fault critical clearing time discrimination method based on improved Softmax regression
  • Power grid fault critical clearing time discrimination method based on improved Softmax regression

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Embodiment

[0062] like figure 1 As shown, the program flow mainly includes two loop bodies: the outer loop continuously reduces the variance σ until it reaches the threshold; the inner loop minimizes the KL divergence; the training process ends after the outer loop is completed, and the optimal model is output.

[0063] Based on the online calculation data of the State Grid Corporation of China from January to October of a certain year, the validity of the method of this topic is verified. In that month, North China-Central China was in the state of network operation, so the online data included the national power grid direct adjustment and all power grid equipment above 220kV in North China and Central China. The main state quantities and statistics of the power grid are shown in the table below; the number of effective samples (number of sections) is 29254. The calculation example adopts the active power of the unit as the input, and the CCT of important lines as the output, and the i...

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Abstract

The invention belongs to the large power grid stabilization and control field and mainly relates to a power grid fault critical clearing time discrimination method based on improved Softmax regression. The method is characterized by modifying a cost function of standard Softmax regression; using normal distribution taking correct classification as a center to be target probability distribution; taking a KL divergence between probability distribution acquired through model calculating and the target probability distribution as the cost function; and through reducing a normal distribution variance and carrying out continuous iteration, acquiring an optimal model.

Description

technical field [0001] The invention belongs to the field of large power grid stability and control, and is a method for automatically identifying stability characteristics corresponding to expected faults in power systems based on machine learning methods and historical calculation data, and in particular relates to a power grid fault criticality based on improved Softmax regression Resection time discrimination method. Background technique [0002] With the rapid improvement of the economic level, the demand for electricity in Chinese society is also becoming stronger. In order to ensure the safe and reliable transmission of electric energy, major projects such as west-to-east power transmission, national networking, and UHV power transmission have been carried out in China's power grid. With the expansion of the grid scale, the security and stability of the grid is becoming more and more difficult to control. Many power grid failures that have occurred in the world show...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 李铁苏安龙唐俊刺曲祖义高凯史东宇何晓洋金晓明田芳崔岱张建姜枫曾辉孙晨光孙文涛朱伟峰詹克明张艳军王顺江周纯莹宁辽逸张宇时卜凡强
Owner STATE GRID LIAONING ELECTRIC POWER RES INST
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