Ocean Systems Engineering

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Predictive control and modeling of a point absorber wave energy harvesting connected to the grid using a LPMSG-based power converter

  • Abderrahmane Berkani (L2GEGI Laboratory, Department of Electrical Engineering, Faculty of Applied Science, University of Tiaret) ;
  • Mofareh Hassan Ghazwani (Department of Mechanical Engineering, Faculty of Engineering, Jazan University) ;
  • Karim Negadi (L2GEGI Laboratory, Department of Electrical Engineering, Faculty of Applied Science, University of Tiaret) ;
  • Lazreg Hadji (Department of Civil Engineering, University of Tiaret) ;
  • Ali Alnujaie (Department of Mechanical Engineering, Faculty of Engineering, Jazan University) ;
  • Hassan Ali Ghazwani (Department of Mechanical Engineering, Faculty of Engineering, Jazan University)
  • Received : 2023.07.02
  • Accepted : 2024.01.14
  • Published : 2024.03.25
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Abstract

In this paper, the authors explore the modeling and control of a point absorber wave energy converter, which is connected to the electric grid via a power converter that is based on a linear permanent magnet synchronous generator (LPMSG). The device utilizes a buoyant mechanism to convert the energy of ocean waves into electrical power, and the LPMSG-based power converter is utilized to change the variable frequency and voltage output from the wave energy converter to a fixed frequency and voltage suitable for the electric grid. The article concentrates on the creation of a predictive control system that regulates the speed, voltage, and current of the LPMSG, and the modeling of the system to simulate its behavior and optimize its design. The predictive model control is created to guarantee maximum energy output and stable grid connection, using Matlab Simulink to validate the proposed strategy, including control side generator and predictive current grid-side converter loops.

Keywords

Acknowledgement

The authors extend their appreciation to the deputyship for Research & Innovation, Ministry of Education in Saudi Arabia for funding this research work through the project number ISP22-5.

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