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Demand response implementation in smart households

2017-05-15Journal article Restricted access
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dc.contributor.authorFotouhi Ghazvini, Mohammad Ali
dc.contributor.authorSoares, João
dc.contributor.authorAbrishambaf, Omid
dc.contributor.authorCastro, Rui
dc.contributor.authorVale, Zita
dc.date.accessioned2017-08-29T14:42:56Z
dc.date.embargo2117
dc.date.issued2017-05-15
dc.description.abstractHome energy management system (HEMS) is essential for residential electricity consumers to participate actively in demand response (DR) programs. Dynamic pricing schemes are not sufficiently effective for end-users without utilizing a HEMS for consumption management. In this paper, an intelligent HEMS algorithm is proposed to schedule the consumption of controllable appliances in a smart household. Electric vehicle (EV) and electric water heater (EWH) are incorporated in the HEMS. They are controllable appliances with storage capability. EVs are flexible energy-intensive loads, which can provide advantages of a dispatchable source. It is expected that the penetration of EVs will grow considerably in future. This algorithm is designed for a smart household with a rooftop photovoltaic (PV) system integrated with an energy storage system (ESS). Simulation results are presented under different pricing and DR programs to demonstrate the application of the HEMS and to verify its’ effectiveness. Case studies are conducted using real measurements. They consider the household load, the rooftop PV generation forecast and the built-in parameters of controllable appliances as inputs. The results exhibit that the daily household energy cost reduces 29.5%–31.5% by using the proposed optimization-based algorithm in the HEMS instead of a simple rule-based algorithm under different pricing schemes.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1016/j.enbuild.2017.03.020pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/10220
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationH2020 MSCA RISE 641794pt_PT
dc.relationANI P2020 3401pt_PT
dc.relationFCT UID/EEA/00760/2013pt_PT
dc.relation.ispartofseriesEnergy and Buildings;Vol. 143
dc.relation.publisherversionhttp://www.sciencedirect.com/science/article/pii/S037877881730823X?via%3Dihubpt_PT
dc.subjectControllable loadpt_PT
dc.subjectDemand responsept_PT
dc.subjectHome energy management systempt_PT
dc.subjectSmart householdpt_PT
dc.subjectThermal storagept_PT
dc.titleDemand response implementation in smart householdspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage148pt_PT
oaire.citation.startPage129pt_PT
oaire.citation.titleEnergy and Buildingspt_PT
oaire.citation.volume143pt_PT
person.familyNameSoares
person.familyNameVale
person.givenNameJoão
person.givenNameZita
person.identifier1043580
person.identifier632184
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication9ece308b-6d79-4cec-af91-f2278dcc47eb
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication.latestForDiscovery9ece308b-6d79-4cec-af91-f2278dcc47eb

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