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Bi-level multi-objective optimization framework for wake escape in floating offshore wind farm

Author

Listed:
  • Huang, Chaoneng
  • Wang, Li
  • Huang, Qian
  • Song, Dongran
  • Yang, Jian
  • Dong, Mi
  • Joo, Young Hoo
  • Duić, Neven

Abstract

Due to the significant motion of wind turbines (WTs) during operation, the coupling of wake effect in floating offshore wind farm (FOWF) is intensified, making the optimization problem combining layout and operation challenging. To address this issue, a bi-level multi-objective intelligent optimization framework for FOWF is proposed. Based on the interaction among operation control, force-induced motion and wake effect, an efficient repositioning model that considers the aerodynamic effect on moveable WT is established. On this basis, a generalized wake control method called “Wake Escape” is defined, taking into account the relationship between optimization variables and objectives in layout design and operation control. To solve the bi-level multi-objective optimization problem of FOWF, FOWFBi-Mopt platform is constructed, on which multi-objective particle swarm optimization and equilibrium optimizer are developed. Additionally, the key parameters and dimensional characteristics are integrated between the layout and operation, facilitating the coordination process of optimization objectives by associating the inner and outer-level algorithms. The simulation results demonstrate that the proposed bi-level optimization framework effectively mitigates the adverse effect of moveable WTs from both layout and operation. Diverse solutions are obtained from Pareto front, achieving comprehensive optimization of FOWF, with the maximum reduction of 1.183 % in the levelized production cost.

Suggested Citation

  • Huang, Chaoneng & Wang, Li & Huang, Qian & Song, Dongran & Yang, Jian & Dong, Mi & Joo, Young Hoo & Duić, Neven, 2025. "Bi-level multi-objective optimization framework for wake escape in floating offshore wind farm," Applied Energy, Elsevier, vol. 377(PD).
    • Handle: RePEc:eee:appene:v:377:y:2025:i:pd:s0306261924020956
    DOI: 10.1016/j.apenergy.2024.124712
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    References listed on IDEAS

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