Publication
Forecasting Refrigerators Consumption to Support their Aggregated Participation in Demand Response
| dc.contributor.author | Faria, Pedro | |
| dc.contributor.author | Jozi, Aria | |
| dc.contributor.author | Vale, Zita | |
| dc.date.accessioned | 2021-03-04T18:24:12Z | |
| dc.date.available | 2021-03-04T18:24:12Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Demand response programs have become very relevant. However, one of the important facts to have a reliable DR program is the creation of a clear and trustable perspective of the load consumption during the upcoming time periods. On another hand, the increment of the energy-based systems and different energy consuming appliances in the last decades results in larger daily energy consumption which creates the unpredictability of the energy demand. This variety of consumption profiles requires not only consideration of the total consumption of each consumer, but more detailed and focused studies on each type of energy consuming devices. Therefore, this paper proposes a system containing a combination of different forecasting and clustering algorithms to predict the power consumption of several refrigerators and aggregate them into certain groups based on the characteristics of their consumption profiles. Sequentially, the obtained results will be aggregated and serve as basis in order to schedule refrigerators in the context of a demand response program. In the case-study, 20000 refrigerators are considered. | pt_PT |
| dc.description.sponsorship | This work has received funding from Portugal 2020 under SPEAR project (NORTE-01-0247-FEDER-040224) and from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project UIDB/00760/2020, and CEECIND/02887/2017. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1109/EEEIC/ICPSEurope49358.2020.9160527 | pt_PT |
| dc.identifier.issn | 978-1-7281-7455-6 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/17288 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | IEEE | pt_PT |
| dc.relation | CEECIND/02887/2017 | pt_PT |
| dc.relation | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9160527 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | Aggregation | pt_PT |
| dc.subject | Demand response | pt_PT |
| dc.subject | Load prediction | pt_PT |
| dc.subject | Refrigerator power consumption | pt_PT |
| dc.title | Forecasting Refrigerators Consumption to Support their Aggregated Participation in Demand Response | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT | |
| oaire.citation.conferencePlace | Madrid, Spain | pt_PT |
| oaire.citation.endPage | 6 | pt_PT |
| oaire.citation.startPage | 1 | pt_PT |
| oaire.citation.title | 2020 IEEE International Conference on Environment and Electrical Engineering and 2020 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Faria | |
| person.familyName | Vale | |
| person.givenName | Pedro | |
| person.givenName | Zita | |
| person.identifier | 632184 | |
| person.identifier.ciencia-id | B212-2309-F9C3 | |
| person.identifier.ciencia-id | 721B-B0EB-7141 | |
| person.identifier.orcid | 0000-0002-5982-8342 | |
| 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.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
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