Research on Wave energy Maximum power based on particle swarm optimization algorithm

Authors

  • Haoyuan Xue
  • Lilong Tian
  • Shengye Zhang
  • Ying An
  • Chen Ma

DOI:

https://doi.org/10.54097/hset.v43i.7431

Keywords:

Runge-Kutta, Wave energy conversion, Particle swarm optimization algorithm.

Abstract

With the increasing demand for energy, non-renewable resources such as coal and oil, which are the main sources of energy, are gradually depleted and have caused serious pollution to the environment. Therefore, the development and utilization of new energy has become a major research topic in today's society; wave energy, as a new energy source, is one of the most abundant energy sources in the ocean and has considerable application prospects. In this paper, the float and oscillator motion models are established by fitting the drape displacement and drape velocity, the longitudinal rocking angular displacement and longitudinal rocking angular velocity of the float and oscillator to the Runge-Kutta method and matlab toolbox. The particle swarm optimization algorithm is then used to determine the maximum output power of the system, and the optimal damping coefficient.

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References

Ding Song, Han Duanfeng. Numerical analysis of the motion model of a pendulum wave energy device [J]. Marine Engineering, 2016, (4): 107 - 117.

Yang Yuneng, Xie Peng, Zheng Xiongbo. Research on power characteristics of point-absorbing wave energy device [J]. Applied Science and Technology, 2015, (2): 75 - 78+82.

E. Y. Tan. Analysis of maximum wave energy capture and power optimization control of wave power system [D]. Guangdong University of Technology, 2021.

Chen Y. Model predictive control of floating wave power system [D]. Tianjin University, 2016.

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Published

14-04-2023