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Design and Optimization of a Wind System Using a Genetic Algorithm

机译:基于遗传算法的风系统设计与优化

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Aims: The aim sought is to design a wind energy system can meet the energy needs of a rural household in minimizing both the economic cost and the energy cost of the system over its life cycle while ensuring continuity in the provision of electrical energy.Study Design: Design of a wind system study.Place and Duration of Study: Department of Mechanical Engineering and Energy, Laboratory Energy and Applied Mechanics, between September 2012 and March 2013.Methodology: We have adopted an approach that requires a combination of field work and scientific work. A survey has been conducted in the locality chosen to know the equipment used to determine the consumption profile; some players were involved in determining the weight we assigned to different criteria. The NSGA-II algorithm, evolutionary genetic type was used in the context of determining the set of optimal solutions of compromise. Design variables used are the wind turbines number, batteries number, wind turbine type, battery type and height of the mast of the wind. The various programs developed have been implemented in Matlab. The method proposed has been applied to a rural household locality of Benin, named Dekin to ensure its power supply.Results: The design made it possible to generate several candidate solutions that are available to the user. There is also the implementation of solutions and promoting the shedding of solutions providing continuous coverage of consumer needs.Conclusion: The multi-objective design of a wind system is not an easy task since antagonistic criteria are taken into account. To this end, we found a compromise by assigning different weight goals. Solutions to economic and energy low cost are found while improving the sevice delivered to the consumer.
机译:目的:旨在设计一种能满足农村家庭能源需求的风能系统,以使其在系统的整个生命周期中的经济成本和能源成本最小化,同时确保电能的连续性。 :风系统研究的设计。研究的地点和持续时间:2012年9月至2013年3月间,机械工程与能源系,实验室能源与应用力学。方法:我们采用了一种将野外工作与科学相结合的方法工作。在选定的地方进行了一次调查,以了解用于确定消费情况的设备;一些参与者参与了确定我们分配给不同标准的权重。 NSGA-II算法(进化遗传类型)用于确定折衷的最优解集。使用的设计变量是风力涡轮机数量,电池数量,风力涡轮机类型,电池类型和风杆的高度。开发的各种程序已在Matlab中实现。所建议的方法已应用于贝宁的一个农村家庭地区,名为Dekin,以确保其供电。结果:设计使生成可供用户使用的几种候选解决方案成为可能。解决方案的实施还可以促进解决方案的流失,从而不断满足消费者的需求。结论:由于考虑到了对立标准,风系统的多目标设计并非易事。为此,我们通过分配不同的体重目标找到了一个折衷方案。找到了经济和能源低成本解决方案,同时改善了交付给消费者的服务。

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