Short-term memory-based control of wind energy conversion systems

被引:0
|
作者
Mei, Xiao-Yan [1 ]
Sun, Zhao
Li, Bin
Yang, Zhi
Song, Yong D.
机构
[1] Chongqing Univ, Coll Automat, Chongqing 630044, Peoples R China
[2] Natl Inst Aerospace, Hampton, VA USA
[3] N Carolina Agr & Tech State Univ, Greensboro, NC 27411 USA
[4] Chongqing Univ, Coll Automat, Chongqing 630044, Peoples R China
[5] N Carolina Agr & Tech State Univ, Dept Elect & Comp Engn, Hampton, VA USA
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Variable speed wind turbine control is essential in extracting maximum electric power out of available wind power. The paper presents a memory-based method for variable speed control of wind energy conversion systems. The fundamental idea behind the method is to use certain memorized information (i.e., current rotor speed tracking error, most recent speed tracking error, and previous control experience) to directly modify the control command. The salient feature of the proposed approach lies in its simplicity in design and implementation. Furthermore, the total required memory space does not grow with time and is much smaller than most existing learning control methods. It is shown that this method, when applied to firing angle control of wind turbines, is able to ensure rotor speed tracking in the presence of varying operation conditions, as verified via computer simulation.
引用
下载
收藏
页码:1517 / 1522
页数:6
相关论文
共 50 条
  • [1] Short-term memory-based object tracking
    Kang, HB
    Cho, SH
    IMAGE ANALYSIS AND RECOGNITION, PT 2, PROCEEDINGS, 2004, 3212 : 597 - 605
  • [2] Multivariate Deep Learning Long Short-Term Memory-Based Forecasting for Microgrid Energy Management Systems
    Moazzen, Farid
    Hossain, M. J.
    ENERGIES, 2024, 17 (17)
  • [3] A Long Short-Term Memory-Based Model for Kinesthetic Data Reduction
    Deng, Qifang
    Mahmoodi, Toktam
    Aghvami, A. Hamid
    IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (19): : 16975 - 16988
  • [4] A long short-term memory-based model for greenhouse climate prediction
    Liu, Yuwen
    Li, Dejuan
    Wan, Shaohua
    Wang, Fan
    Dou, Wanchun
    Xu, Xiaolong
    Li, Shancang
    Ma, Rui
    Qi, Lianyong
    INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2022, 37 (01) : 135 - 151
  • [5] Short-Term Prediction of Wind Power Based on Deep Long Short-Term Memory
    Qu Xiaoyun
    Kang Xiaoning
    Zhang Chao
    Jiang Shuai
    Ma Xiuda
    2016 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2016, : 1148 - 1152
  • [6] Short-term wind power prediction based on combined long short-term memory
    Zhao, Yuyang
    Li, Lincong
    Guo, Yingjun
    Shi, Boming
    Sun, Hexu
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2024, 18 (05) : 931 - 940
  • [7] A Long Short-Term Memory-Based Prototype Model for Drought Prediction
    Villegas-Ch, William
    Garcia-Ortiz, Joselin
    ELECTRONICS, 2023, 12 (18)
  • [8] Performance Analysis of Long Short-Term Memory-Based Markovian Spectrum Prediction
    Radhakrishnan, Niranjana
    Kandeepan, Sithamparanathan
    Yu, Xinghuo
    Baldini, Gianmarco
    IEEE ACCESS, 2021, 9 : 149582 - 149595
  • [9] Long short-term memory-based Malware classification method for information security
    Kang, Jungho
    Jang, Sejun
    Li, Shuyu
    Jeong, Young-Sik
    Sung, Yunsick
    COMPUTERS & ELECTRICAL ENGINEERING, 2019, 77 : 366 - 375
  • [10] Long Short-Term Memory-Based Music Analysis System for Music Therapy
    Li, Ya
    Li, Xiulai
    Lou, Zheng
    Chen, Chaofan
    FRONTIERS IN PSYCHOLOGY, 2022, 13