Publication
DSO Contract Market for Demand Response Using Evolutionary Computation
| dc.contributor.author | Lacerda, Eduardo | |
| dc.contributor.author | Lezama, Fernando | |
| dc.contributor.author | Soares, João | |
| dc.contributor.author | Vale, Zita | |
| dc.date.accessioned | 2023-03-14T11:06:16Z | |
| dc.date.available | 2023-03-14T11:06:16Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | In this article, a cost optimization problem in local energy markets is analyzed considering fixed-term flexibility contracts between the DSO and aggregators. The DSO procures flexibility while aggregators of different types (e.g., conventional demand response or thermo-load aggregators) offer the service. We solve the proposed model using evolutionary algorithms based on the well-known differential evolution (DE). First, a parameter-tuning analysis is done to assess the impact of the DE parameters on the quality of solutions to the problem. Later, after finding the best set of parameters for the "tuned" DE strategies, we compare their performance with other self-adaptive parameter algorithms, namely the HyDE, HyDE-DF, and vortex search algorithms. Results show that with the identification of the best set of parameters to be used for each strategy, the tuned DE versions lead to better results than the other tested EAs. Overall, the algorithms are able to find near-optimal solutions to the problem and can be considered an alternative solver for more complex instances of the model. | pt_PT |
| dc.description.sponsorship | This research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationalization (COMPETE 2020) and National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEIEEE/28983/2017(CENERGETIC), CEECIND/02814/2017 (Joao Soares grant), and UIDB/000760/2020. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1109/CEC45853.2021.9504987 | pt_PT |
| dc.identifier.isbn | 978-1-7281-8393-0 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/22476 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | IEEE | pt_PT |
| dc.relation | PTDC/EEIEEE/28983/2017 | pt_PT |
| dc.relation | Not Available | |
| dc.relation.publisherversion | https://ieeexplore.ieee.org/document/9504987 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | Demand response | pt_PT |
| dc.subject | Aggregator-DSO market | pt_PT |
| dc.subject | Differential evolution | pt_PT |
| dc.subject | Evolutionary computation | pt_PT |
| dc.title | DSO Contract Market for Demand Response Using Evolutionary Computation | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Not Available | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/CEEC IND 2017/CEECIND%2F02814%2F2017%2FCP1417%2FCT0002/PT | |
| oaire.citation.conferencePlace | Kraków, Poland | pt_PT |
| oaire.citation.endPage | 240 | pt_PT |
| oaire.citation.startPage | 233 | pt_PT |
| oaire.citation.title | 2021 IEEE Congress on Evolutionary Computation (CEC) | pt_PT |
| oaire.fundingStream | CEEC IND 2017 | |
| person.familyName | Lezama | |
| person.familyName | Soares | |
| person.familyName | Vale | |
| person.givenName | Fernando | |
| person.givenName | João | |
| person.givenName | Zita | |
| person.identifier | 1043580 | |
| person.identifier | 632184 | |
| person.identifier.ciencia-id | E31F-56D6-1E0F | |
| person.identifier.ciencia-id | 1612-8EA8-D0E8 | |
| person.identifier.ciencia-id | 721B-B0EB-7141 | |
| person.identifier.orcid | 0000-0001-8638-8373 | |
| person.identifier.orcid | 0000-0002-4172-4502 | |
| person.identifier.orcid | 0000-0002-4560-9544 | |
| person.identifier.rid | A-6945-2017 | |
| person.identifier.rid | A-5824-2012 | |
| person.identifier.scopus-author-id | 36810077500 | |
| person.identifier.scopus-author-id | 35436109600 | |
| 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 |
| relation.isAuthorOfPublication | 6a55317b-92c2-404f-8542-c7a73061cc9b | |
| relation.isAuthorOfPublication | 9ece308b-6d79-4cec-af91-f2278dcc47eb | |
| relation.isAuthorOfPublication | ff1df02d-0c0f-4db1-bf7d-78863a99420b | |
| relation.isAuthorOfPublication.latestForDiscovery | 9ece308b-6d79-4cec-af91-f2278dcc47eb | |
| relation.isProjectOfPublication | 7f9ebad6-9f7d-4225-8694-48de17ea8b51 | |
| relation.isProjectOfPublication.latestForDiscovery | 7f9ebad6-9f7d-4225-8694-48de17ea8b51 |