A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

被引：117
|
作者：
Pousinho, H. M. I. [1 ]
Mendes, V. M. F. [2 ]
Catalao, J. P. S. [1 ,3 ]
机构：
[1] Univ Beira Interior, Dept Electromech Engn, P-6201001 Covilha, Portugal
[2] Inst Super Engn Lisboa, Dept Elect Engn & Automat, P-1950062 Lisbon, Portugal
[3] Univ Tecn Lisboa, Inst Super Tecn, Ctr Innovat Elect & Energy Engn, P-1049001 Lisbon, Portugal
来源：
ENERGY CONVERSION AND MANAGEMENT | 2011年 / 52卷 / 01期
关键词：
Wind power; Prediction; Swarm optimization; Neuro-fuzzy; NEURAL-NETWORK APPROACH; SPEED; SYSTEM;
D O I：
10.1016/j.enconman.2010.07.015
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码：397 / 402
页数：6
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