Published March 27, 2017 | Version v1

Agreement technologies applied to transmission towers maintenance

  • 1. Department of Computer Science and Automation Control, University of Salamanca. Plaza de la Merced s/n 37008, Salamanca, Spain
  • 2. bFaculty of Informatics, Department of Artificial Intelligence, Technical University of Madrid. Campus Montegancedo, Boadilla del Monte

Description

Among the most indispensable elements required by a city is electric power and the transmission towers used for its distribution. These towers have underground electrodes which must be reviewed on a regular basis by controlling different parameters to ensure that electrical resistance is in a secure range in order to avoid problems and risks. Using artificial intelligence, it is possible to ensure proper maintenance of the towers by estimating the required values and proposing a reduction in the size of the population sample, which will minimize the cost of operation. The use of an intelligent-agent virtual-organization based architecture is proposed within this working environment. By using mathematical estimation models and agreement based negotiations, the architecture is capable of maximizing estimations and minimizing associated costs. The proposed model has been evaluated with the developed software through a real case study, which permitted us to validate the proposed approach.

Notes

This work has been supported by the European Commission H2020 MSCARISE-2014: Marie Skłodowska-Curie project DREAM-GO Enabling Demand Response for short and real-time Efficient And Market Based Smart Grid Operation - An intelligent and real-time simulation approach ref 641794. The research of Pablo Chamoso has been financed by the Regional Ministry of Education in Castille and Le´on and the European Social Fund (Operational Programme 2014-2020 for Castille and Le´on, EDU/310/2015 BOCYL).

Files

j2-Agreement technologies applied to transmission towers maintenance.pdf

Additional details

Funding

European Commission
DREAM-GO - Enabling Demand Response for short and real-time Efficient And Market Based smart Grid Operation - An intelligent and real-time simulation approach 641794