Wind power forecasting using advanced neural networks models.
Wind power forecasting using advanced neural networks models.
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DOI：
10.1109/60.556376
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发表时间：
1996-12-01
影响因子：
4.9
通讯作者：
Nogaret, EF
中科院分区：
文献类型：
--
作者：
Kariniotakis, GN;Stavrakakis, GS;Nogaret, EF
本文提出了一种基于递归高阶神经网络的风电场功率输出预测模型。该模型的性能优于持久化等简单方法以及文献中的经典方法。预测模型的体系结构被一种新的算法自动优化，该算法取代了通常应用的试错法。最后，给出了所建立的模型在实际风电系统优化运行和管理的先进控制系统中的在线实现。
In this paper, an advanced model, based on recurrent high order neural networks, is developed for the prediction of the power output profile of a wind park. This model outperforms simple methods like persistence, as well as classical methods in the literature. The architecture of a forecasting model is optimised automatically by a new algorithm, that substitutes the usually applied trial-and-error method. Finally, the online implementation of the developed model into an advanced control system for the optimal operation and management of a real autonomous wind-diesel power system, is presented.