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首页> 外文期刊>Journal of Agricultural Science >Computational System for Sizing Wind Energy Generation Systems Using Artificial Neural Networks
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Computational System for Sizing Wind Energy Generation Systems Using Artificial Neural Networks

机译:使用人工神经网络的风能发电系统规模计算系统

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The objective of this work was to develop a computational application for the design of wind power generation systems in small-scale On-Grid and Off-Grid installations, using a user friendly and interactive process. Using artificial intelligence concepts in conjunction with genetic algorithms, to verify the technical and economic viability of the implementation of the wind power generation system. The application coding was done using the languages Java, C, C++ and the database in MySQL language, containing technical specifications and costs of components of a wind system (of this type of system). For the development of neural networks and genetic algorithms, the Encog library was used. The application has proven effective in designing and economic analysis of small wind systems, allowing fast and simple simulation of On-Grid systems and Off-Grid systems. In addition, it proved effective in storing and accessing the information regarding the simulations performed and in the comparison between them, in order to perform a new simulation. Also, it was reliable in the accomplishment of the economic analysis, returning in a clear form the feasibility or not of the implantation of the project.
机译:这项工作的目的是开发一种计算应用程序,它使用用户友好的交互式过程来设计小型并网和离网设施中的风力发电系统。将人工智能概念与遗传算法结合使用,以验证实施风力发电系统的技术和经济可行性。使用Java,C,C ++语言和MySQL语言数据库完成应用程序编码,其中包含技术规范和风力系统(此类系统)的组件成本。为了开发神经网络和遗传算法,使用了Encog库。事实证明,该应用程序在小型风系统的设计和经济分析中非常有效,可以快速,简单地模拟并网系统和离网系统。此外,它被证明在存储和访问与执行的模拟有关的信息以及它们之间的比较以进行新的模拟方面是有效的。此外,它在完成经济分析方面是可靠的,以明确的形式返回了项目植入的可行性与否。

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