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Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm

Author

Listed:
  • Xiaoshi Zhuang

    (School of Automation, Central South University, Changsha 410083, China)

  • Honglue Wan

    (School of Automation, Central South University, Changsha 410083, China)

  • Dongran Song

    (School of Automation, Central South University, Changsha 410083, China)

  • Xinyu Fan

    (School of Automation, Central South University, Changsha 410083, China)

  • Yuchen Wang

    (School of Automation, Central South University, Changsha 410083, China)

  • Qian Huang

    (School of Automation, Central South University, Changsha 410083, China)

  • Jian Yang

    (School of Automation, Central South University, Changsha 410083, China)

Abstract

To address the high complexity layout optimization problem of an offshore wind and wave energy co-generation system, an improved seagull optimization algorithm-based method is proposed. Firstly, the levelized cost of electricity (LCOE) model, based on the whole-life-cycle cost, serves as the optimization objective. Therein, the synergistic effect between wind turbines and wave energy generators is taken into consideration to decouple the problem and establish a two-layer optimization framework. Secondly, the seagull optimization algorithm is enhanced by integrating three strategies: the nonlinear adjustment strategy for control factors, the Gaussian–Cauchy hybrid variational strategy, and the multiple swarm strategy, thereby improving the global search capability. Finally, a case study in the South China Sea validates the effectiveness of the model and algorithm. Using the improved algorithm, the optimal layout of the co-generation system and the optimal wind turbine parameters are obtained. The results indicate that the optimized system achieves a LCOE of 0.6561 CNY/kWh, which is 0.29% lower than that achieved by traditional algorithms. The proposed method provides a reliable technical solution for the economic optimization of the co-generation system.

Suggested Citation

  • Xiaoshi Zhuang & Honglue Wan & Dongran Song & Xinyu Fan & Yuchen Wang & Qian Huang & Jian Yang, 2025. "Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm," Energies, MDPI, vol. 18(11), pages 1-22, May.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:11:p:2846-:d:1667852
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    References listed on IDEAS

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