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首页> 外文期刊>Simulation modelling practice and theory: International journal of the Federation of European Simulation Societies >Estimation of wind turbines optimal number and produced power in a wind farm using an artificial neural network model
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Estimation of wind turbines optimal number and produced power in a wind farm using an artificial neural network model

机译:使用人工神经网络模型估算风电场中的风力涡轮机最佳数量和发电量

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摘要

One of the most significant issues in the design of a new wind farm is the estimation of optimal number of wind turbines that has to be installed in it. The goal of every wind farm designer is the production of the maximum possible power, minimizing the installation cost. The cost can be significantly reduced using the minimum required number of wind turbines for-specific power production, occupying at the same time the least possible acreage of land. In this work an artificial neural network (ANN) model is developed which has the ability to estimate the optimal number of wind turbines and the total produced power in a wind farm. The ANN model's results are compared with those of earlier studies that have followed other approaches, proving that the ANN model is well working and has an acceptable accuracy. The proposed model can be useful in the studies of wind farm designers as a supportive tool for the estimation of the optimal number of wind turbines in a wind farm.
机译:新风电场设计中最重要的问题之一是估算必须安装在其中的风力涡轮机的最佳数量。每位风电场设计人员的目标是生产最大可能的功率,从而最大程度地降低安装成本。通过使用特定发电量所需的最小数量的风力涡轮机,可以显着降低成本,同时占用最少的土地面积。在这项工作中,开发了一种人工神经网络(ANN)模型,该模型具有估算风力涡轮机的最佳数量和风电场总发电量的能力。将ANN模型的结果与采用其他方法的早期研究结果进行比较,证明ANN模型运行良好且具有可接受的准确性。所提出的模型在风电场设计者的研究中可以作为估算风电场中最佳风力涡轮机数量的支持工具而有用。

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