气象参数对太阳能发电影响的人工神经网络建模

V. Abrukov, A. Bobyl, R. Davydov
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引用次数: 1

摘要

介绍了利用人工神经网络对太阳能电站运行进行分析和建模的方法和技术,并对其应用前景进行了讨论。给出了解决各种条件下太阳能发电厂发电量预测问题的实例。比较了基于专业气象站记录的12个气象条件参数的神经网络模型与基于水文气象中心数据的5个参数的神经网络模型的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling with Artificial Neural Networks the Influence of Meteorological Parameters on the Solar Power Plant's Energy Production
Methods and technologies for analyzing and modeling the operation of a solar power plant using artificial neural networks are presented, the prospects for their application are discussed. Examples of solving the problems of forecasting the generation of electrical energy by solar power plants in various conditions are given. A comparison is made of the accuracy of a neural network model based on twelve parameters of meteorological conditions recorded by a special meteorological station and a less accurate neural network based on five parameters that can be taken from the data of the Hydrometeocenter.
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