An optimization method for tidal current turbine array layout based on particle swarm optimization

Tidal current turbine array layout must address the conflict between energy extraction efficiency and spatial utilization under complex wake interactions. However, existing layout methods face limitations in balancing power generation efficiency and marine space occupation. To achieve synergistic optimization of power generation and spatial use, this study introduces the concept of marine space utilization rate (MSUR) and formulates a hybrid multi-objective optimization model (TAM-MPMOS) that simultaneously maximizes total generated energy and optimizes the marine space utilization rate. To solve the TAM-MPMOS model, we develop an Adaptive Lévy flight Chaotic Particle Swarm Optimization (ALCPSO) algorithm, which incorporates a linearly adaptive inertia weight, Lévy flight perturbation, and chaotic mapping into the PSO framework. Based on ALCPSO, we establish a dedicated solution procedure, resulting in a new layout optimization method (TAM-MPMOS_ALCPSO). Performance tests under realistic sea conditions demonstrate that, compared to the conventional staggered layout, our method increases total generated energy by 36.53% and reduces the total centroid distance by 33.56%. Furthermore, for the tidal current turbine array layout optimization problem, ALCPSO significantly outperforms the benchmark algorithms considered in solution quality, convergence stability, and computational efficiency. These results validate the effectiveness and superiority of the proposed method, providing an efficient tool for this class of complex optimization problems.