Agent based control for mierogrids

Dimeas, AL; Hatziargyriou, ND

dc.contributor.author	Dimeas, AL	en
dc.contributor.author	Hatziargyriou, ND	en
dc.date.accessioned	2014-03-01T02:44:25Z
dc.date.available	2014-03-01T02:44:25Z
dc.date.issued	2007	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/31816
dc.subject	Distributed generation	en
dc.subject	Layered learning	en
dc.subject	Mierogrids	en
dc.subject	Multi agent systems	en
dc.subject	Reinforcement learning	en
dc.subject.other	Control theory	en
dc.subject.other	Distributed power generation	en
dc.subject.other	Environmental impact	en
dc.subject.other	Functional analysis	en
dc.subject.other	Multi agent systems	en
dc.subject.other	Reinforcement learning	en
dc.subject.other	Distributed energy resources	en
dc.subject.other	Layered learning	en
dc.subject.other	Microgrids	en
dc.subject.other	Multiagent reinforcement learning	en
dc.subject.other	Energy resources	en
dc.title	Agent based control for mierogrids	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/PES.2007.386064	en
heal.identifier.secondary	http://dx.doi.org/10.1109/PES.2007.386064	en
heal.identifier.secondary	4275830	en
heal.publicationDate	2007	en
heal.abstract	This paper presents a general framework for the control of distributed energy resources organized in Mierogrids. The proposed architecture is based on the agent technology and aims to integrate several functionalities, as well to be adaptable to the complexity and the size of the Microgrid. To achieve this, the idea of layered learning is used, where the various controls and actions of the agents are grouped depending on their effect on the environment. A novel approach called multiagent reinforcement learning is introduced in order to increase the intelligence and the efficiency of the Microgrid. © 2007 IEEE.	en
heal.journalName	2007 IEEE Power Engineering Society General Meeting, PES	en
dc.identifier.doi	10.1109/PES.2007.386064	en