Distributed energy resource and network expansion planning of a CCHP based active microgrid considering demand response programs

dc.contributor.authorVarasteh, Farid
dc.contributor.authorNazar, Mehrdad Setayesh
dc.contributor.authorHeidari, Alireza
dc.contributor.authorShafie-khah, Miadreza
dc.contributor.authorCatalão, João P.S.
dc.contributor.departmentfi=Ei tutkimusalustaa|en=No platform|-
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|-
dc.contributor.orcid0000-0003-1691-5355-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2019-09-18T09:39:15Z
dc.date.accessioned2025-06-25T13:43:57Z
dc.date.available2021-04-01T00:00:20Z
dc.date.issued2019-04-01
dc.description.abstractThis paper addresses the network expansion planning of an active microgrid that utilizes Distributed Energy Resources (DERs). The microgrid uses Combined Cooling, Heating and Power (CCHP) systems with their heating and cooling network. The proposed method uses a bi-level iterative optimization algorithm for optimal expansion and operational planning of the microgrid that consists of different zones, and each zone can transact electricity with the upward utility. The transaction of electricity with the upward utility can be performed based on demand response programs that consist of the time-of-use program and/or direct load control. DERs are CHPs, small wind turbines, photovoltaic systems, electric and cooling storage, gas fired boilers and absorption and compression chillers are used to supply different zones’ electrical, heating, and cooling loads. The proposed model minimizes the system’s investment, operation, interruption and environmental costs; meanwhile, it maximizes electricity export revenues and the reliability of the system. The proposed method is applied to a real building complex and five different scenarios are considered to evaluate the impact of different energy supply configurations and operational paradigm on the investment and operational costs. The effectiveness of the introduced algorithm has been assessed. The implementation of the proposed algorithm reduces the aggregated investment and operational costs of the test system in about 54.7% with respect to the custom expansion planning method.-
dc.description.reviewstatusfi=vertaisarvioitu|en=peerReviewed|-
dc.embargo.lift2021-04-01
dc.embargo.terms2021-04-01
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.format.extent46-
dc.format.pagerange79-105-
dc.identifier.olddbid8816
dc.identifier.oldhandle10024/8242
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/2639
dc.identifier.urnURN:NBN:fi-fe2019091828629-
dc.language.isoeng-
dc.publisherElsevier-
dc.relation.doi10.1016/j.energy.2019.01.015-
dc.relation.ispartofjournalEnergy-
dc.relation.issn1873-6785-
dc.relation.issn0360-5442-
dc.relation.volume172-
dc.rightsCC BY-NC-ND 4.0-
dc.source.identifierWOS: 000464488100008-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/8242
dc.subjectactive microgrid-
dc.subjectdemand response-
dc.subjectdistrict cooling-
dc.subjectdistrict heating-
dc.subject.disciplinefi=Sähkötekniikka|en=Electrical Engineering|-
dc.titleDistributed energy resource and network expansion planning of a CCHP based active microgrid considering demand response programs-
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|en=A1 Peer-reviewed original journal article|sv=A1 Originalartikel i en vetenskaplig tidskrift|-
dc.type.publicationarticle-

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