dc.contributor.author | Song, Dongran | |
dc.contributor.author | Yan, Jiaqi | |
dc.contributor.author | Zeng, Hongda | |
dc.contributor.author | Deng, Xiaofei | |
dc.contributor.author | Yang, Jian | |
dc.contributor.author | Qu, Xilong | |
dc.contributor.author | Rizk-Allah, Rizk M. | |
dc.contributor.author | Snášel, Václav | |
dc.contributor.author | Joo, Young Hoon | |
dc.date.accessioned | 2023-12-14T11:25:01Z | |
dc.date.available | 2023-12-14T11:25:01Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Journal of Marine Science and Engineering. 2023, vol. 11, issue 2, art. no. 279. | cs |
dc.identifier.issn | 2077-1312 | |
dc.identifier.uri | http://hdl.handle.net/10084/151831 | |
dc.description.abstract | This paper proposes a hybrid optimization method to optimize the topological structure
of an offshore-wind-farm power collection system, in which the cable connection, cable selection
and substation location are optimally designed. Firstly, the optimization model was formulated,
which integrates cable investment, energy loss and line construction. Then, the Prim algorithm
was used to initialize the population. A novel hybrid optimization, named PSAO, based on the
merits of the particle swarm optimization (PSO) and aquila optimization (AO) algorithms, was
presented for topological structure optimization, in which the searching characteristics between PSO
and AO are exploited to intensify the searching capability. Lastly, the proposed PSAO method was
validated with a real case. The results showed that compared with GA, AO and PSO algorithms, the
PSAO algorithm reduced the total cost by 4.8%, 3.3% and 2.6%, respectively, while achieving better
optimization efficiency. | cs |
dc.language.iso | en | cs |
dc.publisher | MDPI | cs |
dc.relation.ispartofseries | Journal of Marine Science and Engineering | cs |
dc.relation.uri | https://doi.org/10.3390/jmse11020279 | cs |
dc.rights | © 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution. | cs |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | cs |
dc.subject | offshore wind farm | cs |
dc.subject | topological structure of power collection system | cs |
dc.subject | multivariable joint optimization | cs |
dc.subject | particle swarm aquila optimization algorithm | cs |
dc.title | Topological optimization of an offshore-wind-farm power collection system based on a hybrid optimization methodology | cs |
dc.type | article | cs |
dc.identifier.doi | 10.3390/jmse11020279 | |
dc.rights.access | openAccess | cs |
dc.type.version | publishedVersion | cs |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 11 | cs |
dc.description.issue | 2 | cs |
dc.description.firstpage | art. no. 279 | cs |
dc.identifier.wos | 000941352100001 | |