Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Wind Power Forecasting in Portugal

被引：180

作者：

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

Pousinho, H. M. I. ^{[1
,2
]}

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

机构：

[1] Univ Beira Interior, P-6201001 Covilha, Portugal

[2] IST, Ctr Innovat Elect & Energy Engn, P-1049001 Lisbon, Portugal

[3] Inst Super Engn Lisboa, P-1950062 Lisbon, Portugal

来源：

IEEE TRANSACTIONS ON SUSTAINABLE ENERGY | 2011年 / 2卷 / 01期

关键词：

Forecasting; fuzzy logic; neural networks; swarm optimization; wavelet transform; wind power; NEURAL-NETWORKS; SPEED; PREDICTION; COMBINATION; TRANSFORM; SYSTEM; MODEL;

D O I：

10.1109/TSTE.2010.2076359

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 it occurs today in Portugal, poses new challenges due to its intermittency and volatility. Wind power forecasting plays a key role in tackling these challenges. A novel hybrid approach, combining wavelet transform, particle swarm optimization, and an adaptive-network-based fuzzy inference system, is proposed in this paper for short-term wind power forecasting in Portugal. A thorough comparison is carried out, taking into account the results obtained with seven other approaches. Finally, conclusions are duly drawn.

引用

页码：50 / 59

页数：10

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