A Novel Distributed Paradigm for Energy Scheduling of Islanded Multiagent Microgrids

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorTofighi-Milani, Mahyaren_US
dc.contributor.authorFattaheian-Dehkordi, Sajjaden_US
dc.contributor.authorGholami, Mohammaden_US
dc.contributor.authorFotuhi-Firuzabad, Mahmuden_US
dc.contributor.authorLehtonen, Mattien_US
dc.contributor.departmentDepartment of Electrical Engineering and Automationen
dc.contributor.groupauthorPower Systems and High Voltage Engineeringen
dc.contributor.organizationSharif University of Technologyen_US
dc.date.accessioned2022-11-23T08:03:33Z
dc.date.available2022-11-23T08:03:33Z
dc.date.issued2022en_US
dc.descriptionPublisher Copyright: © 2013 IEEE.
dc.description.abstractRestructuring in power systems has resulted in the development of microgrids (MGs) as entities that could be operated in grid-connected or islanded modes while managing the operation of their systems. On the other hand, privatization and integration of independently operated distributed resources in energy systems have caused the introduction of multi-agent structures. In this regard, new operational management methodologies should be employed by the MG operator (MGO) to efficiently operate the system while addressing the distributed nature of multi-agent structures. Accordingly, this paper aims to provide a new algorithm to operate an islanded multi-agent MG utilizing the peer-to-peer (P2P) management concept, which copes with the distributed nature of the system. Consequently, each agent would independently schedule its respective local resources while participating in the hourly P2P market scheme. Moreover, MGO manages the power transactions among the agents. Furthermore, different types of power generation resources are modeled in the proposed optimization scheme while scenario-based stochastic optimization, as well as the condition-value-at-risk index, are deployed to address the uncertainty and the operational risk associated with the operational optimization of renewable energy resources. Finally, the developed framework is implemented on a 10-bus-MG test system to investigate its effectiveness in the management of the system and also on a 33-bus-MG test system to study its scalability.en
dc.description.versionPeer revieweden
dc.format.extent14
dc.format.extent83636-83649
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationTofighi-Milani, M, Fattaheian-Dehkordi, S, Gholami, M, Fotuhi-Firuzabad, M & Lehtonen, M 2022, ' A Novel Distributed Paradigm for Energy Scheduling of Islanded Multiagent Microgrids ', IEEE Access, vol. 10, pp. 83636-83649 . https://doi.org/10.1109/ACCESS.2022.3197160en
dc.identifier.doi10.1109/ACCESS.2022.3197160en_US
dc.identifier.issn2169-3536
dc.identifier.otherPURE UUID: dc3bb4a2-1bc4-4bb8-8f71-9eea1b59f609en_US
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/dc3bb4a2-1bc4-4bb8-8f71-9eea1b59f609en_US
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85136120005&partnerID=8YFLogxKen_US
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/92137679/A_Novel_Distributed_Paradigm_for_Energy_Scheduling_of_Islanded_Multiagent_Microgrids.pdfen_US
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/117878
dc.identifier.urnURN:NBN:fi:aalto-202211236638
dc.language.isoenen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartofseriesIEEE Accessen
dc.relation.ispartofseriesVolume 10en
dc.rightsopenAccessen
dc.subject.keywordDERsen_US
dc.subject.keywordDistributed energy resourcesen_US
dc.subject.keywordmulti-agent microgriden_US
dc.subject.keywordP2P operational optimizationen_US
dc.subject.keywordpeer-to-peer managementen_US
dc.subject.keywordrenewable energiesen_US
dc.subject.keywordstochastic optimizationen_US
dc.titleA Novel Distributed Paradigm for Energy Scheduling of Islanded Multiagent Microgridsen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion
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