Paper Info
Title
Dealing with Demand in Electric Grids with an Adaptive Consumption Management Platform.
Abstract
The control of consumption in homes and workplaces is an increasingly important aspect if we consider the growing popularity of smart cities, the increasing use of renewable energies, and the policies of the European Union on using energy in an efficient and clean way. These factors make it necessary to have a system that is capable of predicting what devices are connected to an electrical network. For demand management, the system must also be able to control the power supply to these devices. To this end, we propose the use of a multiagent system that includes agents with advanced reasoning and learning capacities. More specifically, the agents incorporate a case-based reasoning system and machine learning techniques. Besides, the multiagent system includes agents that are specialized in the management of the data acquired and the electrical devices. The aim is to adjust the consumption of electricity in networks to the electrical demand, and this will be done by acting automatically on the detected devices. The proposed system provides promising results; it is capable of predicting what devices are connected to the power grid at a high success rate. The accuracy of the system makes it possible to act according to the device preferences established in the system. This allows for adjusting the consumption to the current demand situation, without the risk of important home appliances being switched off.
Year
DOI
Venue
2018
10.1155/2018/4012740
COMPLEXITY
Field
DocType
Volume
Electrical network,Electrical devices,Renewable energy,Industrial engineering,Electricity,Popularity,Demand management,Artificial intelligence,Reasoning system,Mathematics,Machine learning,European union
Journal
2018
ISSN
Citations 
PageRank 
1076-2787
1
0.36
References 
Authors
7
4
Name
Order
Citations
PageRank
Diego M. Jiménez-Bravo111.37
Juan F. De Paz231722.52
Gabriel Villarrubia318324.85
Javier Bajo41451118.96