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
收藏
页码：50 / 59
页数：10
相关论文
共 55 条
  • [1] Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm
    Amjady, N.
    Keynia, F.
    [J]. ENERGY, 2009, 34 (01) : 46 - 57
  • [2] Day ahead price forecasting of electricity markets by a mixed data model and hybrid forecast method
    Amjady, Nima
    Keynia, Farshid
    [J]. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2008, 30 (09) : 533 - 546
  • [3] Applying Wavelets to Short-Term Load Forecasting Using PSO-Based Neural Networks
    Bashir, Z. A.
    El-Hawary, M. E.
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2009, 24 (01) : 20 - 27
  • [4] Entropy and Correntropy Against Minimum Square Error in Offline and Online Three-Day Ahead Wind Power Forecasting
    Bessa, Ricardo J.
    Miranda, Vladimiro
    Gama, Joao
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2009, 24 (04) : 1657 - 1666
  • [5] Catalao JPS, 2009, ENG INTELL SYST ELEC, V17, P5, DOI 10.1109/ISAP.2009.5352853
  • [6] Stochastic Optimization of Wind Turbine Power Factor Using Stochastic Model of Wind Power
    Chen, Peiyuan
    Siano, Pierluigi
    Bak-Jensen, Birgitte
    Chen, Zhe
    [J]. IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2010, 1 (01) : 19 - 29
  • [7] Day-ahead electricity price forecasting using the wavelet transform and ARIMA models
    Conejo, AJ
    Plazas, MA
    Espínola, R
    Molina, AB
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (02) : 1035 - 1042
  • [8] A review on the young history of the wind power short-term prediction
    Costa, Alexandre
    Crespo, Antonio
    Navarro, Jorge
    Lizcano, Gil
    Madsen, Henrik
    Feitosa, Everaldo
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2008, 12 (06) : 1725 - 1744
  • [9] Detecting, categorizing and forecasting large romps in wind farm power output using meteorological observations and WPPT
    Cutler, Nicholas
    Kay, Merlinde
    Jacka, Kieran
    Nielsen, Torben Skov
    [J]. WIND ENERGY, 2007, 10 (05) : 453 - 470
  • [10] A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation
    Damousis, IG
    Alexiadis, MC
    Theocharis, JB
    Dokopoulos, PS
    [J]. IEEE TRANSACTIONS ON ENERGY CONVERSION, 2004, 19 (02) : 352 - 361
123456