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Implementation of Multi-Agent Energy Management for Secondary Control of a Microgrid
  • Yoldas, Yeliz ;
  • Onen, Ahmet ;
  • Alawasa, Khaled ;
  • El Haffar, Abdelsalam ;
  • Ahshan, Razzaqul ;
  • Islam, Md Rabiul ;
  • Muyeen, S. M. ;
  • Noorfatima, Nadya ;
  • Jung, Jaesung
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dc.contributor.authorYoldas, Yeliz-
dc.contributor.authorOnen, Ahmet-
dc.contributor.authorAlawasa, Khaled-
dc.contributor.authorEl Haffar, Abdelsalam-
dc.contributor.authorAhshan, Razzaqul-
dc.contributor.authorIslam, Md Rabiul-
dc.contributor.authorMuyeen, S. M.-
dc.contributor.authorNoorfatima, Nadya-
dc.contributor.authorJung, Jaesung-
dc.date.issued2023-01-01-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/36924-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85183600663&origin=inward-
dc.description.abstractThe multi-agent energy management system (EMS) is needed to coordinate multiple agents of a microgrid to provide efficient operation of the system. In this study, multi-agent EMS is seen as the middle controller between primary and tertiary control levels. It is responsible for determining the relevant set points based on data gathered from the tertiary control level and sending them to the appropriate primary control level agents. The main objective of this paper is to propose a new optimization model for multi-agent EMS to minimize errors between the forecasted and real-time data at every predetermined time interval. Rather than using a traditional centralized microgrid controller to determine the dispatch of resources, a new framework-based multi-agent coordination is proposed to achieve the following objectives: minimizing load shedding, maximizing load dispatch and reliability, providing frequency, and maintaining voltage stability.-
dc.language.isoeng-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.subject.meshControl level-
dc.subject.meshDynamic energy managements-
dc.subject.meshMicrogrid-
dc.subject.meshMulti agent energy management-
dc.subject.meshMultiple agents-
dc.subject.meshOptimal controls-
dc.subject.meshPoint-based-
dc.subject.meshPrimary control-
dc.subject.meshSecondary control-
dc.subject.meshSetpoints-
dc.titleImplementation of Multi-Agent Energy Management for Secondary Control of a Microgrid-
dc.typeConference-
dc.citation.conferenceDate2023.10.27. ~ 2023.10.29.-
dc.citation.conferenceName2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2023-
dc.citation.edition2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2023-
dc.citation.title2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2023-
dc.identifier.bibliographicCitation2023 IEEE International Conference on Applied Superconductivity and Electromagnetic Devices, ASEMD 2023-
dc.identifier.doi10.1109/asemd59061.2023.10368896-
dc.identifier.scopusid2-s2.0-85183600663-
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=10368384-
dc.subject.keywordDynamic energy management-
dc.subject.keywordmicrogrid-
dc.subject.keywordoptimal control-
dc.subject.keywordsecondary control-
dc.type.otherConference Paper-
dc.description.isoafalse-
dc.subject.subareaSurfaces, Coatings and Films-
dc.subject.subareaInstrumentation-
dc.subject.subareaEnergy Engineering and Power Technology-
dc.subject.subareaElectrical and Electronic Engineering-
dc.subject.subareaMechanical Engineering-
dc.subject.subareaElectronic, Optical and Magnetic Materials-
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