Research on an improved model predictive current control for direct-drive wave energy converters with linear generators

被引:1
|
作者
Huang, Lei [1 ]
Wei, Lai [1 ]
Liu, Jing [2 ]
Yang, Jianlong [1 ]
Zhang, Xiaoyu [1 ]
机构
[1] Southeast Univ, Sch Elect Engn, 2 Sipailou, Nanjing, Peoples R China
[2] China Univ Petr, Coll Mech & Elect Engn, Qingdao, Peoples R China
基金
中国国家自然科学基金;
关键词
current control; direct-drive wave energy converter; extended voltage vectors; model predictive control; permanent magnet linear generator; CONVERSION SYSTEMS; POWER;
D O I
10.1049/rpg2.12702
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper deals with the current control strategy of a permanent magnet linear generator (PMLG) for a direct-drive wave energy converter (DDWEC). As the mover is in a linear reciprocating motion, the reference of the controller of the generator is dynamic fluctuations with the mover movement under maximum power point tracking (MPPT) conditions. Therefore, the dynamic requirements of the controller become higher. To increase dynamic control performance, an improved model predictive current control (IMPCC) strategy is proposed here. Through a three-step cascaded optimization algorithm, the target voltage vector is optimized from the three dimensions of the sector of the voltage vector, the angle of the voltage vector and the length of the voltage vector. The target voltage vector is output to the three-phase rectifier by using SVPWM to complete the entire control process. Simulation and experimental results show that the proposed control strategy effectively reduces the current ripple and the vibration of PMLG and improves the stability of DDWEC.
引用
收藏
页码:1670 / 1679
页数:10
相关论文
共 50 条
  • [31] Direct Model Predictive Current Control For Matrix Converters
    Saha, Jaydeep
    Ayad, Ayman
    Kennel, Ralph
    2017 INTERNATIONAL CONFERENCE ON NASCENT TECHNOLOGIES IN ENGINEERING (ICNTE-2017), 2017,
  • [32] Operation and Sizing Aspects of Converters for Wind Energy Systems equipped with Direct-Drive, Permanent Magnet Generators
    Di Gerlando, Antonino
    Foglia, Giovanni Maria
    Perini, Roberto
    Ubaldini, Mario
    ICEM: 2008 INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES, VOLS 1- 4, 2009, : 1104 - 1109
  • [33] Variable Coefficient Model Predictive Control Strategy for Direct-drive Wave Energy Conversion System Considering Field Weakening Effect
    Qin C.
    Jiang A.
    Sun Y.
    Jin M.
    Ding W.
    Wu F.
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2024, 44 (09): : 3531 - 3540
  • [34] Research on a Direct-Drive Wave Energy Converter Using an Outer-PM Linear Tubular Generator
    Huang, Lei
    Hu, Minqiang
    Chen, Zhongxian
    Yu, Haitao
    Liu, Chunyuan
    IEEE TRANSACTIONS ON MAGNETICS, 2017, 53 (06)
  • [35] Research on a direct-drive wave energy converter using Outer-PM linear tubular generator
    Huang, Lei
    Hu, Minqiang
    Yang, Jian
    Chen, Minshuo
    2016 IEEE CONFERENCE ON ELECTROMAGNETIC FIELD COMPUTATION (CEFC), 2016,
  • [36] Research on Improved Permanent Magnet Linear Synchronous Motor for Direct-Drive Application
    Wen, Cheng
    Liu, Jin
    Wang, Weiming
    Liu, Junyu
    Zhao, Zhiyan
    Liu, Jingna
    IEEE TRANSACTIONS ON MAGNETICS, 2019, 55 (10)
  • [37] Integrated structural and electromagnetic design of direct-drive linear machines for wave energy
    Crozier, R.
    Mueller, M.
    IET RENEWABLE POWER GENERATION, 2012, 6 (03) : 137 - 148
  • [38] Design and Experiment Analysis of a Direct-Drive Wave Energy Converter with a Linear Generator
    Zhang, Jing
    Yu, Haitao
    Shi, Zhenchuan
    ENERGIES, 2018, 11 (04)
  • [39] Modelling and Analysis of the Two-Body Direct-Drive Wave Energy Converter and Optimal Energy Extraction Method Based on Model Predictive Control
    Huang X.
    Lin Z.
    Xiao X.
    Diangong Jishu Xuebao/Transactions of China Electrotechnical Society, 2024, 39 (02): : 445 - 454
  • [40] Adaptive Model Predictive Control of Wave Energy Converters
    Zhan, Siyuan
    Na, Jing
    Li, Guang
    Wang, Bin
    IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2020, 11 (01) : 229 - 238