Extended Hybrid Wind Power Forecasting Approach to Short-Term Decisions

被引:0
|
作者
Osorio, Gerardo J. [1 ]
Lotfi, Mohamed [2 ,3 ]
Campos, Vasco M. A. [4 ]
Catalao, Joao P. S. [2 ,3 ]
机构
[1] C MAST UBI, Covilha, Portugal
[2] Univ Porto, Fac Engn, Porto, Portugal
[3] INESC TEC, Porto, Portugal
[4] Redes Energet Nacionais REN SGPS SA, P-1700177 Lisbon, Portugal
关键词
Adaptive neuro-fuzzy inference system; Hybrid forecasting approach; Monte Carlo simulation; Short-term decision; Wind power;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The advantages of wind power integration over other renewable resources are well-known information and the natural results are the massive worldwide integration. Such massive integration, without the correct management together with conventional generation leads to an augmented complexity and the inflexibility of conventional power systems. For several reasons, forecasting tools are one of the most valuable tools in the power systems field, because they helps to decide in advance the way to manage correctly and with profits the electrical mix production. In this work, an extended hybrid wind power forecasting approach, with probabilistic features, is proposed to forecast twenty-four hours-ahead, considering only real historical wind power data. To validate the proposed forecasting approach, a comparison with other validated models is performed to offer a fair and proportional analysis. The outcomes show that the suggested forecasting approach performs adequately even considering the reduced data available as input.
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页数:6
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