Paper Info
Title
Agent-based tool to reduce the maintenance cost of energy distribution networks.
Abstract
There has been continuous research in the energy distribution sector because of its huge impact on modern societies. Nonetheless, aerial high voltage power lines are still supported by old transmission towers which involve some serious risks. Those risks may be avoided with periodic and expensive reviews. The main objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. More specifically, the work is focused on reducing the number of periodic reviews of transmission towers to avoid step and touch potentials, which are very dangerous for humans. A virtual organization-based multi-agent system is proposed in conjunction with different artificial intelligence methods and algorithms. The developed system is able to propose a sample of transmission towers from a selected set to be reviewed. The system ensures that the whole set will have similar values without needing to review all the transmission towers. As a result of this work, a website application is provided to manage all the review processes and all the transmission towers of Spain. It allows the companies that review the transmission towers to initiate a new review process for a whole line or area, while the system indicates the transmission towers to review. The system is also able to recommend the best place to locate a new transmission tower or the best type of structure to use when a new transmission tower must be used.
Year
DOI
Venue
2018
10.1007/s10115-017-1120-7
Knowl. Inf. Syst.
Keywords
Field
DocType
Virtual organizations,Transmission towers,Maintenance,Case-based reasoning
Transmission (mechanics),Data mining,High voltage power lines,Computer science,Simulation,Transmission tower,Electric power transmission,Case-based reasoning,Periodic graph (geometry),Reliability engineering,Energy distribution,Virtual organization
Journal
Volume
Issue
ISSN
54
3
0219-1377
Citations 
PageRank 
References 
0
0.34
14
Authors
4
Name
Order
Citations
PageRank
Pablo Chamoso19424.80
Juan F. De Paz231722.52
Javier Bajo31451118.96
Gabriel Villarrubia418324.85