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Method and system for predicting cost of operation, maintenance and repair of primary equipment of power grid

A technology of primary equipment and maintenance cost, applied in the field of electric power engineering, can solve problems such as difficult linear expression, and achieve the effect of easy management and control

Inactive Publication Date: 2018-07-27
STATE GRID ZHEJIANG ELECTRIC POWER +1
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a GRA-EFA-GA-BPNN-based power grid primary equipment for the defect that the relationship between the operation and maintenance cost of the primary equipment of the existing power grid and various influencing factors is difficult to be expressed linearly. The operation and maintenance cost prediction method can accurately and reasonably estimate the operation and maintenance cost of primary equipment in the power grid, so that grid enterprises can effectively manage and control the operation and maintenance cost of primary equipment in the power grid

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  • Method and system for predicting cost of operation, maintenance and repair of primary equipment of power grid

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Embodiment 1

[0051] This embodiment provides a method for predicting the cost of operation and maintenance of primary equipment in the power grid, such as figure 1 As shown, it includes the following steps:

[0052] (1) Analysis of the gray relational degree of factors affecting the cost of operation and maintenance of primary equipment in the power grid: use gray relational analysis to calculate the degree of correlation between the primary influencing factors and the cost of operation and maintenance of primary equipment in the power grid, and then sort the influencing factors according to the degree of correlation , to get the selected indicators to ensure the correlation between the screened influencing factors and the cost of primary equipment operation and maintenance of the power grid.

[0053] (2) Exploratory factor analysis of factors affecting the cost of operation and maintenance of primary equipment in the power grid: on the basis of gray relational analysis, in order to reduce...

Embodiment 2

[0084] This embodiment provides a power grid primary equipment operation and maintenance cost prediction system, which includes:

[0085] Gray relational degree analysis unit: used for gray relational degree analysis of factors affecting the cost of primary equipment operation and maintenance of the power grid;

[0086] Exploratory factor analysis unit: used for exploratory factor analysis of factors affecting the cost of primary equipment operation and maintenance of the power grid;

[0087] Initial weight and threshold optimization unit: based on genetic algorithm, used for BP neural network initial weight and threshold optimization;

[0088] Power grid primary equipment operation and maintenance cost prediction unit: based on BP neural network, used for power grid primary equipment operation and maintenance cost prediction;

[0089] The main factors affecting the operation and maintenance cost of power grid primary equipment are extracted by gray relational analysis unit a...

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Abstract

The invention discloses a method and system for predicting the cost of operation, maintenance and repair of primary equipment of a power grid. The prediction method of the invention comprises performing a gray correlation analysis of factors affecting the cost of operation, maintenance and repair of primary equipment of a power grid; performing an exploratory factor analysis of the factors affecting the cost of operation, maintenance and repair of the primary equipment of the power grid; and performing initial weight and threshold optimization of a BP neural network based on a genetic algorithm; predicting the cost of operation, maintenance and repair of the primary equipment of the power grid based on the BP neural network: combining with an input index obtained by the exploratory factoranalysis, relying on the initial weight and threshold obtained by the genetic algorithm, using the BP neural network to complete the training, obtaining a power grid primary equipment operation, maintenance and repair cost prediction model, and analyzing the error between predicted and actual values. The method and system of the invention can accurately and reasonably estimate the cost of operation, maintenance and repair of the primary equipment of the power grid, and allow power grid enterprises to easily and effectively manage and control the cost of operation, maintenance and repair of theprimary equipment of the power grid.

Description

technical field [0001] The invention belongs to the technical field of electric power engineering, and relates to a GRA-EFA-GA-BPNN-based method and system for predicting the operation and maintenance cost of primary equipment in a power grid. Background technique [0002] The cost of operation and maintenance of primary equipment of the power grid is an important part of the investment of power grid enterprises. In order to formulate the best investment strategy, it is necessary to accurately and reasonably estimate the cost of operation, maintenance and maintenance of primary equipment of the power grid. However, the operation and maintenance cost of primary equipment in the power grid is affected by various factors such as society, economy, policy, and resources, and the mechanism of each factor is complex, which makes the relationship between the operation and maintenance cost of primary equipment in the power grid and various influencing factors difficult to be linear. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/00G06Q50/06G06N3/08G06N3/12
CPCG06N3/084G06N3/123G06Q10/20G06Q50/06
Inventor 俞敏方鹏沈洁陈俊刘福炎童军陈佳金淋
Owner STATE GRID ZHEJIANG ELECTRIC POWER
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