A Fuzzy Neural Network Approach to Estimate PMSG based and DFIG based Wind Turbines' Power Generation

被引:0
|
作者
Demirdelen, Tugce [1 ]
Bakmaz, Emel [2 ]
Tumay, Mehmet [2 ]
机构
[1] Adana Sci & Technol Univ, Dept Elect & Elect Engn, Saricam Adana, Turkey
[2] Cukurova Univ, Dept Elect & Elect Engn, Adana, Turkey
关键词
DFIG; Fuzzy Neural Network; PMSG; Wind Power;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Neural networks and fuzzy systems are amalgamate their advantages and to eliminate its individual disadvantages. Neural networks have its computational characteristics of learning in the fuzzy systems and receive from them the interpretation and clarity of systems representation. Thus, the disadvantages of the fuzzy systems are fulfilled by the capacities of the neural networks. These techniques are complementary, which prove its use together. This is called fuzzy neural networks In this paper, a fuzzy neural network is applied to estimate PMSG based and DFIG based wind turbines' power generation. The obtained results showed that this model can be used to predict wind turbine power generation and performance analysis both two type turbines in a simple, reliable and accurate way.
引用
收藏
页码:101 / 106
页数:6
相关论文
共 50 条
  • [41] High-Frequency Resonance of DFIG-Based Wind Generation under Weak Power Network
    Zhu, Lin
    Hu, Xinge
    Li, Shuyong
    2018 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON), 2018, : 2719 - 2724
  • [42] Central Difference Kalman Filter Approach Based Decentralized Dynamic States Estimator for DFIG Wind Turbines in Power Systems
    Fan, Xinqi
    Yu, Samson Shenglong
    Chau, Tat Kei
    Fernando, Tyrone
    Townsend, Christopher
    Iu, Herbert H. C.
    2019 9TH INTERNATIONAL CONFERENCE ON POWER AND ENERGY SYSTEMS (ICPES), 2019,
  • [43] Application of Mind Evolutionary Computation based fuzzy neural network in Variable-speed Wind Turbines
    Liu Qingsong
    Qian Suxiang
    Xiong Yuansheng
    PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE, 2012, : 6798 - 6803
  • [44] Neural Network Based Voltage and Frequency Controller for Isolated Wind Power Generation
    Singh, Bhim
    Sharma, Shailendra
    IETE JOURNAL OF RESEARCH, 2011, 57 (05) : 467 - 477
  • [45] Modeling of small wind turbines based on PMSG with diode bridge for sensorless maximum power tracking
    Urtasun, Andoni
    Sanchis, Pablo
    San Martin, Idoia
    Lopez, Jesus
    Marroyo, Luis
    RENEWABLE ENERGY, 2013, 55 : 138 - 149
  • [46] Study of a Simplified Model for DFIG-Based Wind Turbines
    Lima, F. K. A.
    Luna, A.
    Rodriguez, P.
    Watanabe, E. H.
    Aredes, M.
    2009 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION, VOLS 1-6, 2009, : 749 - +
  • [47] Control of PMSG-Based Wind Turbines for System Inertial Response and Power Oscillation Damping
    Wang, Yi
    Meng, Jianhui
    Zhang, Xiangyu
    Xu, Lie
    IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2015, 6 (02) : 565 - 574
  • [48] Power and Current Limiting Control of Wind Turbines Based on PMSG Under Unbalanced Grid Voltage
    Liu, Jun
    Zhao, Chencong
    Xie, Zhouhua
    IEEE ACCESS, 2021, 9 : 9873 - 9883
  • [49] Power Quality Improvement of Microgrid with Cascaded Controller-Based PMSG Used in Wind Turbines
    Praiselin, W. J.
    Edward, J. Belwin
    ADVANCES IN SMART GRID AND RENEWABLE ENERGY, 2018, 435 : 477 - 483
  • [50] A comprehensive sensorless control of DFIG-based wind turbines
    Abedinzadeh, Taher
    Tohidi, Sajjad
    COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING, 2016, 35 (01) : 27 - 43