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Model Predictive Control Strategy of Wind Turbine Based on LSTM

  • Yan Liu
  • , Lin Zhu
  • , Huihui Song*
  • , Tao Deng
  • , Panpan Yang
  • , Weimin Wu
  • *Corresponding author for this work
  • State Power Investment Corporation Limited
  • School of New Energy, Harbin Institute of Technology Weihai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Model Predictive Control is an advanced control method commonly applied in industrial control systems. The basic idea is to combine the existing model and use the state and constraints of the current time system to predict the behavior state and output variables of the period of time in the future, so as to achieve more accurate and efficient dynamic regulation. Based on MPC in this paper, the MPC method based on Long Short- Term Memory is introduced to control the machine side and network side of wind turbine and compared with MPC method to verify the speed and stability of MPC method based on LSTM. The findings indicate that the approach utilizing LSTM MPC can adapt to the system changes more intelligently and quickly, accurately complete the control goal of the wind turbine, ensure that the wind turbine can achieve efficient and stable operation state, and significantly improve the stability and efficiency of the wind farm grid connection system.

Original languageEnglish
Title of host publication2024 11th International Forum on Electrical Engineering and Automation, IFEEA 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1050-1053
Number of pages4
ISBN (Electronic)9798331516611
DOIs
StatePublished - 2024
Externally publishedYes
Event11th International Forum on Electrical Engineering and Automation, IFEEA 2024 - Shenzhen, China
Duration: 22 Nov 202424 Nov 2024

Publication series

Name2024 11th International Forum on Electrical Engineering and Automation, IFEEA 2024

Conference

Conference11th International Forum on Electrical Engineering and Automation, IFEEA 2024
Country/TerritoryChina
CityShenzhen
Period22/11/2424/11/24

Keywords

  • LSTM
  • Model Predictive Control
  • Wind turbine
  • deep learning
  • insert
  • stability of grid-connected system

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