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dc.date.accessioned 2012-09-12T16:49:37Z
dc.date.available 2012-09-12T16:49:37Z
dc.date.issued 2009
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/20883
dc.description.abstract In this article we analyze two kinds of metaheuristic algorithms applied to wind farm optimization. The basic idea is to utilize CHC (a sort of GA) and GPSO (a sort of PSO) algorithms to obtain an acceptable configuration of wind turbines in the wind farm that maximizes the total output energy and minimize the number of wind turbines used. The energy produced depends of the farm geometry, wind conditions and the terrain where it is settled. In this work we will analyze three study farm scenarios with different wind speeds and we will apply both algorithms to analyze the performance of the algorithms and the behavior of the computed wind farm designs. en
dc.format.extent 50-59 es
dc.language en es
dc.subject CHC en
dc.subject Energía Eólica es
dc.subject Optimization es
dc.subject geometric particle swarm optimization en
dc.subject Heuristic methods es
dc.title GA and PSO applied towind energy optimization en
dc.type Objeto de conferencia es
sedici.creator.person Alba, Enrique es
sedici.creator.person Bilbao, Martín es
sedici.description.note Presentado en el X Workshop Agentes y Sistemas Inteligentes es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2009-10
sedici.relation.event XV Congreso Argentino de Ciencias de la Computación es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)