Parameter identification based on equivalent modeling of AWS wave farm
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    Abstract:

    Parameter identification based time domain equivalent modeling method of wave farm is proposed. The wave data measured in any measuring point of the Archimedes wave swing (AWS)-based wave farm and the total output power of the wave farm are used to identify the parameters of the equivalent mechanical model by Particle swarm optimization(PSO) . The detailed model of the wave farm considering wake and time-lag effects are built via MATLAB/Simulink. Simulations are performed using multiple sets of measured wave data to validate the effectiveness of the proposed method. The simulation results show that the equivalent parameters identified under different measured data are stable and reasonable. For the equivalent model identified by the first set of measured data, the output power of the equivalent model and the detailed model fit well under the other three sets of measured wave data.

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History
  • Received:November 07,2018
  • Revised:December 11,2018
  • Adopted:January 24,2019
  • Online: March 28,2019
  • Published: March 28,2019