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dc.contributor.authorGarcía, Marcel
dc.contributor.authorAguilar, Jose 
dc.contributor.authorRodríguez-Moreno, Maria
dc.date.accessioned2023-02-20T18:11:03Z
dc.date.available2023-02-20T18:11:03Z
dc.date.issued2023-02-01
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dc.identifier.issn2169-3536es
dc.identifier.urihttps://hdl.handle.net/20.500.12761/1674
dc.description.abstractSatisfying energy demand has become a global problem that is on the rise due to population growth, infrastructure deterioration, a decline in fossil fuel sources, and high costs for investment, among others. Smart grids, in addition to those challenges that they have at the level of energy generation, have other management challenges derived from the great diversity of components that make them up, such as energy storage systems (batteries, capacitors, etc.), the different types of consumers (controllable, non-controllable loads) and prosumers (electric vehicles, self-sustaining buildings, micro-grid, etc.), among others. Consequently, a distributed control problem is presented, mainly oriented to the coordination of its components. A possible solution is to achieve the participation of each component when conditions are more favorable, such as prioritizing production with renewable energy sources, or taking advantage of prosumers so that they can meet local demand, among other things. Therefore, new strategies with a distributed approach such as bio-inspired emergent controls are necessary. The objective of this work is the specification of an emergent control approach to coordinate a smart grid. This approach allows the coordination of the energy supply in various operating scenarios. The results obtained demonstrate a perfect synchronization between the different smart grid components (agents), prioritizing renewable energy sources, regardless of the operational context (for example, in cases of failures, unsuitable environmental conditions, etc.).es
dc.language.isoenges
dc.publisherIEEE Societyes
dc.titleA Bioinspired Emergent Control for Smart Gridses
dc.typejournal articlees
dc.journal.titleIEEE Accesses
dc.type.hasVersionVoRes
dc.rights.accessRightsopen accesses
dc.volume.number11es
dc.identifier.doi10.1109/ACCESS.2023.3238572es
dc.page.final7520es
dc.page.initial7503es
dc.subject.keywordEmergent Control, Smart Grid, Bioinspired algorithms, Distributed Artificial Intelligence.es
dc.description.refereedTRUEes
dc.description.statuspubes


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