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dc.contributor.authorC. Kongnamen_US
dc.contributor.authorS. Nuchprayoonen_US
dc.date.accessioned2018-09-04T04:45:13Z-
dc.date.available2018-09-04T04:45:13Z-
dc.date.issued2010-11-01en_US
dc.identifier.issn09601481en_US
dc.identifier.other2-s2.0-77954816571en_US
dc.identifier.other10.1016/j.renene.2010.02.020en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=77954816571&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/50757-
dc.description.abstractThe control problem of a wind turbine involves the determination of rotor speed and tip-speed ratio to maximize power and energy capture from the wind. The problem can be formulated as a nonlinear programming problem with the annual energy generation as the objective function. The wind speed distribution is modeled as the Weibull distribution. The Weibull shape and scale parameters are assigned to be stochastic in response to limited wind data and variability nature of the wind. It is proposed to apply particle swarm optimization to solve for optimum rotor speed under fixed-speed operation and optimum tip-speed ratio under variable-speed operation. The optimum rotor speed varies with the wind speed distribution, while the optimum tip-speed ratio does not depend on the wind speed distribution. It can be concluded from the simulation results that both the wind power and energy are more dependent of the Weibull scale parameter than the Weibull shape parameter. This implies that the wind power and energy are more dependent of the mean wind speed than the speed distribution. © 2010 Elsevier Ltd.en_US
dc.subjectEnergyen_US
dc.titleA particle swarm optimization for wind energy control problemen_US
dc.typeJournalen_US
article.title.sourcetitleRenewable Energyen_US
article.volume35en_US
article.stream.affiliationsDepartment of Electrical Maintenanceen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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