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Demand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential House

2019Journal article Open access
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dc.contributor.authorFaia, R.
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.contributor.authorSpinola, João
dc.date.accessioned2021-02-04T17:17:37Z
dc.date.available2021-02-04T17:17:37Z
dc.date.issued2019
dc.description.abstractDemand response as a distributed resource has proved its significant potential for power systems. It is capable of providing flexibility that, in some cases, can be an advantage to suppress the unpredictability of distributed generation. The ability for participating in demand response programs for small or medium facilities has been limited; with the new policy regulations this limitation might be overstated. The prosumers are a new entity that is considered both as producers and consumers of electricity, which can provide excess production to the grid. Moreover, the decision-making in facilities with different generation resources, energy storage systems, and demand flexibility becomes more complex according to the number of considered variables. This paper proposes a demand response optimization methodology for application in a generic residential house. In this model, the users are able to perform actions of demand response in their facilities without any contracts with demand response service providers. The model considers the facilities that have the required devices to carry out the demand response actions. The photovoltaic generation, the available storage capacity, and the flexibility of the loads are used as the resources to find the optimal scheduling of minimal operating costs. The presented results are obtained using a particle swarm optimization and compared with a deterministic resolution in order to prove the performance of the model. The results show that the use of demand response can reduce the operational daily cost.pt_PT
dc.description.sponsorshipThe present work was done and funded in the scope of the following projects: SIMOCE Project (P2020-23575) and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT. Ricardo Faia is supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with PhD grant reference SFRH/BD/133086/2017.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/en12091645pt_PT
dc.identifier.issn1996-1073
dc.identifier.urihttp://hdl.handle.net/10400.22/16887
dc.language.isoengpt_PT
dc.publisherMDPIpt_PT
dc.relationResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
dc.relationApoio à decisão para participação em mercados de energia elétrica
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/12/9/1645pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/pt_PT
dc.subjectDemand responsept_PT
dc.subjectDistributed generationpt_PT
dc.subjectParticle swarm optimizationpt_PT
dc.subjectProsumerpt_PT
dc.titleDemand Response Optimization Using Particle Swarm Algorithm Considering Optimum Battery Energy Storage Schedule in a Residential Housept_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleResearch Group on Intelligent Engineering and Computing for Advanced Innovation and Development
oaire.awardTitleApoio à decisão para participação em mercados de energia elétrica
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FEEA%2F00760%2F2019/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F133086%2F2017/PT
oaire.citation.issue9pt_PT
oaire.citation.startPage1645pt_PT
oaire.citation.titleEnergiespt_PT
oaire.citation.volume12pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameFaia
person.familyNameFaria
person.familyNameVale
person.givenNameRicardo Francisco Marcos
person.givenNamePedro
person.givenNameZita
person.identifier78FtZwIAAAAJ
person.identifier632184
person.identifier.ciencia-id9B12-19F6-D6C7
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0002-1053-7720
person.identifier.orcid0000-0002-5982-8342
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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