Characterization of Daily Wind Farm Power Fluctuations Using Wavelet Transform

被引：1
|
作者：
Chu, Xiaodong [1 ]
Zhang, Wen [1 ,2 ]
Nwachukwu, Tochi [2 ]
Hiskens, Ian A. [2 ]
机构：
[1] Shandong Univ, Sch Elect Engn, Jinan, Peoples R China
[2] Univ Wisconsin, Dept Elect & Comp Engn, Madison, WI USA
来源：
ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 4, PROCEEDINGS | 2008年
关键词：
D O I：
10.1109/ICNC.2008.133
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
With the increase of wind power installed capacities, the cost of integration is large due to the intermittent nature of wind energy. To accommodate wind farm power fluctuations, additional control measures are required. Accurate characterization of the fluctuations paves the way for optimal control design. In identifying localized characteristics of the signal, wavelet transform provides a suitable tool. Data gathered at a wind farm of New Mexico are studied with its daily output variations characterized using wavelet transform.
引用
收藏
页码：481 / +
页数：2
相关论文
共 50 条
  • [41] A short-term forecasting of wind power outputs using the enhanced wavelet transform and arimax techniques
    Ahn, EunJi
    Hur, Jin
    RENEWABLE ENERGY, 2023, 212 : 394 - 402
  • [42] Wind Power Forecasting Using Wavelet Transform and General Regression Neural Network for Ontario Electricity Market
    Saroha, Sumit
    Aggarwal, Sanjeev K.
    RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING, 2020, 13 (01) : 16 - 26
  • [43] A novel hybrid approach for predicting wind farm power production based on wavelet transform, hybrid neural networks and imperialist competitive algorithm
    Aghajani, Afshin
    Kazemzadeh, Rasool
    Ebrahimi, Afshin
    ENERGY CONVERSION AND MANAGEMENT, 2016, 121 : 232 - 240
  • [44] Extreme learning approach with wavelet transform function for forecasting wind turbine wake effect to improve wind farm efficiency
    Mladenovic, Igor
    Markovic, Dusan
    Milovancevic, Milos
    Nikolic, Miroljub
    ADVANCES IN ENGINEERING SOFTWARE, 2016, 96 : 91 - 95
  • [45] Power measurement using the wavelet transform of analytic signals
    Croes, T
    Gherasim, C
    Van den Keybus, J
    Ghijselen, J
    Driesen, J
    Belmans, R
    2004 11TH INTERNATIONAL CONFERENCE ON HARMONICS AND QUALITY OF POWER, 2004, : 338 - 342
  • [46] Protection of power transformers by using continuous wavelet transform
    Ozgonenel, O.
    CIRCUITS AND SYSTEMS FOR SIGNAL PROCESSING , INFORMATION AND COMMUNICATION TECHNOLOGIES, AND POWER SOURCES AND SYSTEMS, VOL 1 AND 2, PROCEEDINGS, 2006, : 1106 - 1109
  • [47] Detection of power quality disturbances using wavelet transform
    Department of Electrical Engineering, Netaji Subhash Engineering College, Kolkata, West Bengal, India
    不详
    World Acad. Sci. Eng. Technol., 2009, (869-873):
  • [48] Differential Protection of Power Transformers Using The Wavelet Transform
    Medeiros, R. P.
    Costa, F. B.
    Fernandes, J. F.
    2014 IEEE PES GENERAL MEETING - CONFERENCE & EXPOSITION, 2014,
  • [49] Power system fault monitoring using wavelet transform
    Charfi, F
    Al-Haddad, K
    François, B
    PESC 04: 2004 IEEE 35TH ANNUAL POWER ELECTRONICS SPECIALISTS CONFERENCE, VOLS 1-6, CONFERENCE PROCEEDINGS, 2004, : 919 - 924
  • [50] Smoothening of Wind Farm Output Fluctuations Using New Pitch Controller
    Hasan, A. G. M. Rakibul
    Sheikh, M. R. I.
    2016 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER & TELECOMMUNICATION ENGINEERING (ICECTE), 2016,
12345