Differential evolution with a new encoding mechanism for optimizing wind farm layout

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dc.contributor.author Wang, Yong en
dc.contributor.author Liu, Hao en
dc.contributor.author Long, Huan en
dc.contributor.author Zhang, Zijun en
dc.contributor.author Yang, Shengxiang en
dc.date.accessioned 2017-08-11T09:58:25Z
dc.date.available 2017-08-11T09:58:25Z
dc.date.issued 2017-07-11
dc.identifier.citation Wang, 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, 2017 en
dc.identifier.uri http://hdl.handle.net/2086/14414
dc.description.abstract This 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.iso en_US en
dc.publisher IEEE Press en
dc.subject Wind farm layout en
dc.subject optimization en
dc.subject wake effect en
dc.subject encoding mechanism en
dc.subject differential evolution en
dc.title Differential evolution with a new encoding mechanism for optimizing wind farm layout en
dc.type Article en
dc.identifier.doi https://doi.org/10.1109/tii.2017.2743761
dc.researchgroup Centre for Computational Intelligence en
dc.peerreviewed Yes en
dc.funder EPSRC (Engineering and Physical Sciences Research Council) en
dc.funder EU Horizon 2020 Marie Sklodowska-Curie Individual Fellowships en
dc.funder National Natural Science Foundation of China en
dc.funder National Natural Science Foundation of China en
dc.projectid EP/K001310/1 en
dc.projectid 661327 en
dc.projectid 61673397 en
dc.projectid 61673331 en
dc.cclicence CC-BY-NC-ND en
dc.date.acceptance 2017-07-11 en
dc.exception.reason open access article en


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