Publication
Demand Response Contextual Remuneration of Prosumers with Distributed Storage
| dc.contributor.author | Silva, Cátia | |
| dc.contributor.author | Faria, Pedro | |
| dc.contributor.author | Ribeiro, Bruno | |
| dc.contributor.author | Gomes, Luis | |
| dc.contributor.author | Vale, Zita | |
| dc.date.accessioned | 2023-02-02T10:39:37Z | |
| dc.date.available | 2023-02-02T10:39:37Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Prosumers are emerging in the power and energy market to provide load flexibility to smooth the use of distributed generation. The volatile behavior increases the production prediction complexity, and the demand side must take a step forward to participate in demand response events triggered by a community manager. If balance is achieved, the participants should be compensated for the discomfort caused. The authors in this paper propose a methodology to optimally manage a community, with a focus on the remuneration of community members for the provided flexibility. Four approaches were compared and evaluated, considering contextual tariffs. The obtained results show that it was possible to improve the fairness of the remuneration, which is an incentive and compensation for the loss of comfort. The single fair remuneration approach was more beneficial to the community manager, since the total remuneration was lower than the remaining approaches (163.81 m.u. in case study 3). From the prosumers’ side, considering a clustering method was more advantageous, since higher remuneration was distributed for the flexibility provided (196.27 m.u. in case study 3). | pt_PT |
| dc.description.sponsorship | This work is supported by FEDER Funds through COMPETE program and by National Funds through FCT under projects UIDP/00760/2020, UIDB/00760/2020, and CEECIND/01423/2021. Cátia Silva is supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with Ph.D. grant reference SFRH/BD/144200/2019. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.3390/s22228877 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.22/22100 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | MDPI | pt_PT |
| dc.relation | CEECIND/01423/2021 | pt_PT |
| dc.relation | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| dc.relation | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| dc.relation | Effective DR gathering and deployment for intensive renewable integration using aggregation and machine learning | |
| dc.relation.publisherversion | https://www.mdpi.com/1424-8220/22/22/8877 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | Contextual remuneration | pt_PT |
| dc.subject | Battery energy storage | pt_PT |
| dc.subject | Demand response | pt_PT |
| dc.subject | Optimal management | pt_PT |
| dc.subject | Smart grids | pt_PT |
| dc.title | Demand Response Contextual Remuneration of Prosumers with Distributed Storage | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| oaire.awardTitle | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| oaire.awardTitle | Effective DR gathering and deployment for intensive renewable integration using aggregation and machine learning | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F00760%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT//SFRH%2FBD%2F144200%2F2019/PT | |
| oaire.citation.issue | 22 | pt_PT |
| oaire.citation.startPage | 8877 | pt_PT |
| oaire.citation.title | Sensors | pt_PT |
| oaire.citation.volume | 22 | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Silva | |
| person.familyName | Faria | |
| person.familyName | Vale | |
| person.givenName | Cátia | |
| person.givenName | Pedro | |
| person.givenName | Zita | |
| person.identifier | 632184 | |
| person.identifier.ciencia-id | 5318-DCFD-218D | |
| person.identifier.ciencia-id | B212-2309-F9C3 | |
| person.identifier.ciencia-id | 6F19-CB63-C8A8 | |
| person.identifier.ciencia-id | 721B-B0EB-7141 | |
| person.identifier.orcid | 0000-0001-8306-4568 | |
| person.identifier.orcid | 0000-0002-5982-8342 | |
| person.identifier.orcid | 0000-0002-8597-3383 | |
| person.identifier.orcid | 0000-0002-4560-9544 | |
| person.identifier.rid | A-5824-2012 | |
| person.identifier.scopus-author-id | 7004115775 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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