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Multi-objective robust optimization to solve energy scheduling in buildings under uncertainty

2017Conference object Open access
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dc.contributor.authorSoares, João
dc.contributor.authorVale, Zita
dc.contributor.authorBorges, Nuno
dc.contributor.authorLezama, Fernando
dc.contributor.authorKagan, Nelson
dc.date.accessioned2021-03-09T11:46:02Z
dc.date.available2021-03-09T11:46:02Z
dc.date.issued2017
dc.description.abstractWith the high penetration of renewable generation in Smart Grids (SG), the uncertainty behavior associated with the forecast of weather conditions possesses a new degree of complexity in the Energy Resource Management (ERM) problem. In this paper, a Multi-Objective Particle Swarm Optimization (MOPSO) methodology is proposed to solve ERM problem in buildings with penetration of Distributed Generation (DG) and Electric Vehicles (EVs) and considering the uncertainty of photovoltaic (PV) generation. The proposed methodology aims to maximize profits while minimizing CO 2 emissions. The uncertainty of PV generation is modeled with the use of Monte Carlo simulation in the evaluation process of the MOPSO core. Also, a robust optimization approach is adopted to select the best solution for the worst-case scenario of PV generation. A case study is presented using a real building facility from Brazil, to verify the effectiveness of the implemented robust MOPSO.pt_PT
dc.description.sponsorshipThis work has received funding from the Project NetEffiCity (ANI|P2020 18015), and from FEDER Funds through COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/ISAP.2017.8071417pt_PT
dc.identifier.isbn978-1-5090-4000-1
dc.identifier.urihttp://hdl.handle.net/10400.22/17321
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.relationANI|P2020 18015pt_PT
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8071417pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectEnergy Resources Managementpt_PT
dc.subjectCO2 Emissionspt_PT
dc.subjectMulti-Objective Particle Swarm Optimizationpt_PT
dc.subjectRobust Optimizationpt_PT
dc.titleMulti-objective robust optimization to solve energy scheduling in buildings under uncertaintypt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/5876/UID%2FEEA%2F00760%2F2013/PT
oaire.citation.conferencePlaceSan Antonio, TX, USApt_PT
oaire.citation.endPage6pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.title19th International Conference on Intelligent System Application to Power Systems (ISAP)pt_PT
oaire.fundingStream5876
person.familyNameSoares
person.familyNameVale
person.familyNameLezama
person.givenNameJoão
person.givenNameZita
person.givenNameFernando
person.identifier1043580
person.identifier632184
person.identifier.ciencia-id1612-8EA8-D0E8
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.ciencia-idE31F-56D6-1E0F
person.identifier.orcid0000-0002-4172-4502
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0001-8638-8373
person.identifier.ridA-5824-2012
person.identifier.ridA-6945-2017
person.identifier.scopus-author-id35436109600
person.identifier.scopus-author-id7004115775
person.identifier.scopus-author-id36810077500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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