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dc.contributor.authorWang, Yongen
dc.contributor.authorLiu, Haoen
dc.contributor.authorLong, Huanen
dc.contributor.authorZhang, Zijunen
dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2017-08-11T09:58:25Z
dc.date.available2017-08-11T09:58:25Z
dc.date.issued2017-07-11
dc.identifier.citationWang, Y., Liu, H., Long, H., Zhang, Z. and Yang, S. (2017) Differential evolution with a new encoding mechanism for optimizing wind farm layout. IEEE Transactions on Industrial Informatics, in press, 2017en
dc.identifier.urihttp://hdl.handle.net/2086/14414
dc.description.abstractThis paper presents a differential evolution algorithm with a new encoding mechanism for efficiently solving the optimal layout of the wind farm, with the aim of maximizing the power output. In the modeling of the wind farm, the wake effects among different wind turbines are considered and the Weibull distribution is employed to estimate the wind speed distribution. In the process of evolution, a new encoding mechanism for the locations of wind turbines is designed based on the characteristics of the wind farm layout. This encoding mechanism is the first attempt to treat the location of each wind turbine as an individual. As a result, the whole population represents a layout. Compared with the traditional encoding, the advantages of this encoding mechanism are twofold: 1) the dimension of the search space is reduced to two, and 2) a crucial parameter (i.e., the population size) is eliminated. In addition, differential evolution serves as the search engine and the caching technique is adopted to enhance the computational efficiency. The comparative analysis between the proposed method and seven other state-of-the-art methods is conducted based on two wind scenarios. The experimental results indicate that the proposed method is able to obtain the best overall performance, in terms of the power output and execution time.en
dc.language.isoen_USen
dc.publisherIEEE Pressen
dc.subjectWind farm layouten
dc.subjectoptimizationen
dc.subjectwake effecten
dc.subjectencoding mechanismen
dc.subjectdifferential evolutionen
dc.titleDifferential evolution with a new encoding mechanism for optimizing wind farm layouten
dc.typeArticleen
dc.identifier.doihttps://doi.org/10.1109/tii.2017.2743761
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderEPSRC (Engineering and Physical Sciences Research Council)en
dc.funderEU Horizon 2020 Marie Sklodowska-Curie Individual Fellowshipsen
dc.funderNational Natural Science Foundation of Chinaen
dc.funderNational Natural Science Foundation of Chinaen
dc.projectidEP/K001310/1en
dc.projectid661327en
dc.projectid61673397en
dc.projectid61673331en
dc.cclicenceCC-BY-NC-NDen
dc.date.acceptance2017-07-11en
dc.exception.reasonopen access articleen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


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