Publication
WCCI/GECCO 2020 Competition on Evolutionary Computation in the Energy Domain: An overview from the winner perspective
dc.contributor.author | Rodríguez-González, Ansel Y. | |
dc.contributor.author | Lezama, Fernando | |
dc.contributor.author | Martínez-López, Yoan | |
dc.contributor.author | Madera, Julio | |
dc.contributor.author | Soares, João | |
dc.contributor.author | Vale, Zita | |
dc.date.accessioned | 2023-02-02T12:45:36Z | |
dc.date.available | 2023-02-02T12:45:36Z | |
dc.date.issued | 2022 | |
dc.description.abstract | Evolutionary computation is attracting attention in the energy domain as an alternative to tackle inherent mathematical complexity of some problems related to high-dimensionality, non-linearity, non-convexity, multimodality, or discontinuity of the search space. In this context, the research community launched the 2020 ”Competition on Evolutionary Computation in the Energy Domain: Smart Grid Applications” and an associated simulation framework to evaluate the performance of state-of-the-art evolutionary algorithms solving real-world problems. The competition includes two testbeds: (1) Day-ahead energy resource management problem in smart grids under uncertain environments; and (2) Bi-level optimization of end-users’ bidding strategies in local energy markets. This paper describes the general framework of the competition, the two testbeds, and the evolutionary algorithms that participated. A special section is dedicated to the winner approach, CUMDANCauchy++, a cellular Estimation Distribution Algorithm (EDA). A thorough analysis of the results reveals that, led by CUMDANCauchy++, the top three algorithms form a block of approaches all based on cellular EDAs. Moreover, for testbed 2, in which CUMDANCauchy++ did not achieve the best performance, the winner approach is also based on EDAs. The outcomes of the competition show that CUMDANCauchy++ is an effective algorithm solving both testbeds, and EDAs emerge as an algorithm class with promising performance for solving smart grid applications. | pt_PT |
dc.description.sponsorship | This research was partially supported by the National Council of Science and Technology (CONACYT) under project Cátedras CONACYT 2143. Also, this work has received funding from FEDER Funds through COMPETE program and from National Funds through (FCT) under the projects UIDB/00760/2020 and MAS-Society (PTDC /EEI-EEE/28954/2017). Joao Soares was supported by the grant CEECIND/02814/2017 from National Funds through FCT . | pt_PT |
dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
dc.identifier.doi | 10.1016/j.asoc.2022.109162 | pt_PT |
dc.identifier.uri | http://hdl.handle.net/10400.22/22116 | |
dc.language.iso | eng | pt_PT |
dc.peerreviewed | yes | pt_PT |
dc.publisher | Elsevier | pt_PT |
dc.relation | PTDC /EEI-EEE/28954/2017 | pt_PT |
dc.relation | Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development | |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S1568494622004148?via%3Dihub | pt_PT |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
dc.subject | Evolutionary algorithms | pt_PT |
dc.subject | Estimation distribution algorithms | pt_PT |
dc.subject | Optimization | pt_PT |
dc.subject | Smart grids | pt_PT |
dc.subject | Statistical analysis | pt_PT |
dc.title | WCCI/GECCO 2020 Competition on Evolutionary Computation in the Energy Domain: An overview from the winner perspective | 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.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00760%2F2020/PT | |
oaire.citation.startPage | 109162 | pt_PT |
oaire.citation.title | Applied Soft Computing | pt_PT |
oaire.citation.volume | 125 | pt_PT |
oaire.fundingStream | 6817 - DCRRNI ID | |
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 | closedAccess | pt_PT |
rcaap.type | article | pt_PT |
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