Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/52070
Title: | Swarm intelligence for frequency management in smart grids | Authors: | Evora, Jose Hernández Cabrera, José Juan Hernandez, Mario Dzemyda, Gintautas Kurasova, Olga Kremers, Enrique |
UNESCO Clasification: | 120304 Inteligencia artificial | Keywords: | Swarm intelligence Multi-agent system Behaviour function Energy system Demand side management, et al |
Issue Date: | 2015 | Project: | Framework Para la Simulación de la Gestión de Mercado y Técnica de Redes Eléctricas Insulares Basado en Agentes Inteligentes. Caso de la Red Eléctrica de Gran Canaria. | Journal: | Informatica | Abstract: | A secure and high-quality operation of power grids requires frequency to be managed to keep it stable around a reference value. The deviation of the frequency from this reference value is caused by the imbalance between the active power produced and consumed. In the Smart Grid paradigm, the balance can be achieved by adjusting the demand to the production constraints, instead of the other way round. In this paper, an swarm intelligence-based approach for frequency management is proposed. It is grounded on the idea that a swarm is composed of decentralised individual agents (particles) and that each of them interacts with other ones via a shared environment. Three swarm intelligence-based policies ensure a decentralised frequency management in the smart power grid, where agents of swarm are making decisions and acting on the demand side. Policies differ in behaviour function of agents. Finally, these policies are evaluated and compared using indicators that point out their advantages. | URI: | http://hdl.handle.net/10553/52070 | ISSN: | 0868-4952 | DOI: | 10.15388/Informatica.2015.56 | Source: | Informatica (Netherlands) [ISSN 0868-4952], v. 26 (3), p. 419-434 |
Appears in Collections: | Artículos |
SCOPUSTM
Citations
5
checked on Nov 24, 2024
WEB OF SCIENCETM
Citations
5
checked on Nov 24, 2024
Page view(s)
132
checked on Sep 29, 2024
Download(s)
190
checked on Sep 29, 2024
Google ScholarTM
Check
Altmetric
Share
Export metadata
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.