Supercharge Your Innovation With Domain-Expert AI Agents!

Electric transmission line icing prediction model based on neural network and fuzzy logic algorithm

A fuzzy logic algorithm and neural network technology, applied in the field of transmission line icing combination prediction model, can solve problems such as bad micro-meteorological conditions and inapplicability of the global model

Inactive Publication Date: 2014-06-11
NANJING INST OF TECH
View PDF4 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the frequent occurrence of ice-covered tower collapses, most of the cases are caused by the severe micro-meteorological conditions in this area, so the global model is not applicable in this area

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Electric transmission line icing prediction model based on neural network and fuzzy logic algorithm
  • Electric transmission line icing prediction model based on neural network and fuzzy logic algorithm
  • Electric transmission line icing prediction model based on neural network and fuzzy logic algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0061] The solution of the present invention is: a combination prediction model of transmission line icing based on neural network and fuzzy logic algorithm. Analysis and prediction of micro-meteorological data, including the following steps:

[0062] Such as figure 1 Shown is a transmission line icing prediction model based on neural network and fuzzy logic algorithm, which is characterized in that it includes the following steps:

[0063] S01: Read in the micrometeorological parameters of historical micrometeorological points to form a training sample;

[0064] S02: Determine the parameters of the BP neural network model, and use the data processing formula to continuously correct the weight w of the network ij and threshold θ j ;

[0065] S03: Complete the iterative process of the neural network to obtain the basic component of ice thickness o pi ;

[0066] S04: Read in the location information of the tower, including the altitude, the distance from the water vapor in...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an electric transmission line icing prediction model based on a neural network and a fuzzy logic algorithm. The model comprises the following steps: reading micro meteorological parameters to form a training sample, modifying the weight of a network, introducing a threshold, acquiring the fundamental component of the icing thickness, reading position information of a pole tower, establishing an altitude subordinating degree function and a large area moisture distance subordinating degree function, establishing an error correction subordinating degree function, forming a fuzzy rule bank so as to obtain correction coefficients through defuzzification, and combining the calculation result of the neural network and the fuzzy logic compensation result. The electric transmission line icing prediction model with geographical location information is high in prediction precision when being compared with a conventional global model and a single BP (Back Propagation) neural network, and has a good effect in practical application.

Description

technical field [0001] The invention proposes a combination forecasting model of transmission line icing based on a neural network and a fuzzy logic algorithm, which belongs to the field of power system safety protection. Background technique [0002] As the artery of the power system, the transmission line provides a channel for the collaborative operation between the user's electricity consumption and the power grid, and its important position is beyond doubt. However, due to long-term exposure to the wild, the line not only has natural aging and deterioration problems, but also is a huge carrier of environmental disasters, making it the most vulnerable part of the power system. Especially in winter, lines in some areas are heavily icing, causing faults such as twisted towers, collapsed towers, disconnected lines, etc., which cannot guarantee the sustainability of power supply for users and have a serious impact on production and life. At the same time, it also increases ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/02G06N7/02
Inventor 王娇许家浩张惠刚迟翔
Owner NANJING INST OF TECH
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com