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Demand Response of Residential Houses Equipped with PV-Battery Systems: An Application Study Using Evolutionary Algorithms

2020-05Journal article Open access
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dc.contributor.authorLezama, Fernando
dc.contributor.authorFaia, Ricardo
dc.contributor.authorFaria, Pedro
dc.contributor.authorVale, Zita
dc.date.accessioned2021-09-20T14:41:12Z
dc.date.available2021-09-20T14:41:12Z
dc.date.issued2020-05
dc.description.abstractHouseholds equipped with distributed energy resources, such as storage units and renewables, open the possibility of self-consumption of on-site generation, sell energy to the grid, or do both according to the context of operation. In this paper, a model for optimizing the energy resources of households by an energy service provider is developed. We consider houses equipped with technologies that support the actual reduction of energy bills and therefore perform demand response actions. A mathematical formulation is developed to obtain the optimal scheduling of household devices that minimizes energy bill and demand response curtailment actions. In addition to the scheduling model, the innovative approach in this paper includes evolutionary algorithms used to solve the problem under two optimization approaches: (a) the non-parallel approach combine the variables of all households at once; (b) the parallel-based approach takes advantage of the independence of variables between households using a multi-population mechanism and independent optimizations. Results show that the parallel-based approach can improve the performance of the tested evolutionary algorithms for larger instances of the problem. Thus, while increasing the size of the problem, namely increasing the number of households, the proposed methodology will be more advantageous. Overall, vortex search overcomes all other tested algorithms (including the well-known differential evolution and particle swarm optimization) achieving around 30% better fitness value in all the cases, demonstrating its effectiveness in solving the proposed problempt_PT
dc.description.sponsorshipThis work has received funding from FEDER Funds through COMPETE program and from National Funds through (FCT) under the projects UID/EEA/00760/2019, and grants CEECIND/02887/2017 and SFRH/BD/133086/2017. This work has received funding from H2020 in scope of DOMINOES project.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/en13102466pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.22/18441
dc.language.isoengpt_PT
dc.publisherMDPIpt_PT
dc.relationSmart Distribution Grid: a Market Driven Approach for the Next Generation of Advanced Operation Models and Services
dc.relation.publisherversionhttps://www.mdpi.com/1996-1073/13/10/2466pt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectDemand responsept_PT
dc.subjectEnergy service providerpt_PT
dc.subjectEnergy storage systempt_PT
dc.subjectEvolutionary algorithmspt_PT
dc.subjectOptimizationpt_PT
dc.subjectPhotovoltaic generationpt_PT
dc.titleDemand Response of Residential Houses Equipped with PV-Battery Systems: An Application Study Using Evolutionary Algorithmspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleSmart Distribution Grid: a Market Driven Approach for the Next Generation of Advanced Operation Models and Services
oaire.awardURIinfo:eu-repo/grantAgreement/EC/H2020/771066/EU
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/POR_NORTE/68959/PT
oaire.citation.issue10pt_PT
oaire.citation.startPage2466pt_PT
oaire.citation.titleEnergiespt_PT
oaire.citation.volume13pt_PT
oaire.fundingStreamH2020
oaire.fundingStreamPOR_NORTE
person.familyNameLezama
person.familyNameFaia
person.familyNameFaria
person.familyNameVale
person.givenNameFernando
person.givenNameRicardo Francisco Marcos
person.givenNamePedro
person.givenNameZita
person.identifier78FtZwIAAAAJ
person.identifier632184
person.identifier.ciencia-idE31F-56D6-1E0F
person.identifier.ciencia-id9B12-19F6-D6C7
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.orcid0000-0001-8638-8373
person.identifier.orcid0000-0002-1053-7720
person.identifier.orcid0000-0002-5982-8342
person.identifier.orcid0000-0002-4560-9544
person.identifier.ridA-6945-2017
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id36810077500
person.identifier.scopus-author-id7004115775
project.funder.identifierhttp://doi.org/10.13039/501100008530
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameEuropean Commission
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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