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Power distribution network planning method based on association rule driving

A technology for distribution network planning and distribution network, which is applied in neural learning methods, electrical digital data processing, biological neural network models, etc.

Active Publication Date: 2019-07-26
SICHUAN UNIV
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  • Abstract
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  • Claims
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Problems solved by technology

[0003] Aiming at the above-mentioned deficiencies in the prior art, a distribution network planning method driven by association rules provided by the present invention solves the problem of association analysis between distribution network transformation measures and reliability indicators

Method used

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  • Power distribution network planning method based on association rule driving
  • Power distribution network planning method based on association rule driving
  • Power distribution network planning method based on association rule driving

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Embodiment

[0044] like figure 1 As shown, the present invention provides a distribution network planning method driven by association rules, and its implementation method is as follows:

[0045] (S1) Determine the reliability index of the distribution network transformation measures;

[0046] (S2) According to the reliability index, train the association rules between the reliability index and the distribution network transformation measures through the neural network;

[0047] (S3) Solve the association rules through the distribution network planning model, so as to realize the planning of the distribution network.

[0048]In this embodiment, the method for determining the reliability index of the distribution network transformation measures is as follows: the reliability of the distribution network transformation measures is determined by using statistical values ​​of indicators such as the average power outage time of the user within a year, the expected power shortage of the system,...

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Abstract

The invention provides a power distribution network planning method based on association rule driving. The power distribution network planning method comprises the following steps: determining a reliability index of a power distribution network transformation measure; training an association rule between a power distribution network transformation measure and the reliability index through a neuralnetwork; and solving the association rule through a power distribution network planning optimization model driven based on the association rule, thereby realizing the planning of the power distribution network. Through the design, the correlation analysis problem between the power distribution network transformation measure and the reliability index is solved. According to the method, the solvingprocess is simple, the solving speed is high, the operability is high, and the planning scheme can be flexibly selected according to the reliability requirement of each region on the power distribution network.

Description

technical field [0001] The invention belongs to the technical field of distribution network planning, and in particular relates to a distribution network planning method driven by association rules. Background technique [0002] Association rule analysis has great advantages in discovering potential laws of problems and improving computing efficiency. Commonly used algorithms include regression analysis, SVM, and artificial neural networks. Among them, artificial neural networks have better self-learning ability and high-speed optimization. It is widely used in the evaluation of distribution network power supply performance indicators. In terms of distribution network planning, some studies have proposed multi-layer Hopfield neural network models, corresponding energy functions and parameter selection rules for the characteristics of radial operation of urban power grids, and some studies have used cascaded correlation neural networks to analyze the impact of interruptible l...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q50/06G06F17/50G06N3/08
CPCG06Q10/06393G06Q10/0637G06Q50/06G06N3/086G06F30/20Y04S10/50
Inventor 向月刘俊勇柴雁欣魏翔宇
Owner SICHUAN UNIV
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