Hybrid intelligent approach for short-term wind power forecasting in Portugal

被引：57

作者：

Catalao, J. P. S. ^{[1
,2
]}

Pousinho, H. M. I. ^{[1
]}

Mendes, V. M. F. ^{[3
]}

机构：

[1] Univ Beira Interior, Dept Electromech Engn, P-6201001 R Fonte Do Lameiro, Covilha, Portugal

[2] Inst Super Tecn, Ctr Innovat Elect & Energy Engn, P-1049001 Lisbon, Portugal

[3] Inst Super Engn Lisboa, Dept Elect Engn & Automat, P-1950062 Lisbon, Portugal

来源：

IET RENEWABLE POWER GENERATION | 2011年 / 5卷 / 03期

关键词：

NEURAL-NETWORK APPROACH; WAVELET TRANSFORM; ARIMA MODELS; MARKET; SPEED; GENERATION; PREDICTION; RESOURCE; SYSTEMS; PRICES;

D O I：

10.1049/iet-rpg.2009.0155

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges because of its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this study, a hybrid intelligent approach is proposed for short-term wind power forecasting in Portugal. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Conclusions are duly drawn.

引用

页码：251 / 257

页数：7

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