Investigation of Data Size Variability in Wind Speed Prediction Using AI Algorithms
Investigation of Data Size Variability in Wind Speed Prediction Using AI Algorithms
复制标题
人工智能算法在风速预测中的数据量变异性研究
DOI：
10.1080/01969722.2020.1827796
复制
发表时间：
2020-10-02
影响因子：
1.7
通讯作者：
Oladunni, Timothy
中科院分区：
文献类型：
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作者：
Ehsan, M. A.;Shahirinia, Amir;Oladunni, Timothy
燃烧化石燃料发电是全球变暖的主要原因之一。可再生能源是生产电能和减少电力工业排放的可行替代方案。它们为消费者提供了在当地生产电力并在现场使用的机会，从而减少了对集中发电的依赖。尽管广泛可用，主要挑战之一是以更翔实的方式了解其特征。风能高度依赖于间歇性风速剖面。本文提出了风速预测，简化风电场规划和可行性研究。12种人工智能算法被用于从收集的气象参数预测风速。比较了模型的性能，以确定风速预测精度和不同规模的数据集的模型比较。结果表明，最有效的算法根据数据大小而变化。
Electricity generation from burning fossil fuel is one of the major contributors to global warming. Renewable energy sources are a viable alternative to produce electrical energy and to reduce the emission from power industry. They have unlocked opportunities for consumers to produce electricity locally and use it on-site that reduces dependency on centralized generation. Despite the widespread availability, one of the major challenges is to understand their characteristics in a more informative way. Wind energy is highly dependent on the intermittent wind speed profile. This paper proposes the prediction of wind speed that simplifies wind farm planning and feasibility study. Twelve artificial intelligence algorithms were used for wind speed prediction from collected meteorological parameters. The model performances were compared to determine the wind speed prediction accuracy and model comparison for different sizes of data set. The results show, the most effective algorithm varies based on the data size.