In consideration of the resource wasted by unreasonable layout scheme of tidal current turbines, which would influence the ratio of cost and power output, particle swarm optimization algorithm is introduced and improved in the paper. In order to solve the problem of optimal array of tidal turbines, the discrete particle swarm optimization (DPSO) algorithm has been performed by re-defining the updating strategies of particles’ velocity and position. This paper analyzes the optimization problem of micrositing of tidal current turbines by adjusting each turbine’s position, where the maximum value of total electric power is obtained at the maximum speed in the flood tide and ebb tide. Firstly, the best installed turbine number is generated by maximizing the output energy in the given tidal farm by the Farm/Flux and empirical method. Secondly, considering the wake effect, the reasonable distance between turbines, and the tidal velocities influencing factors in the tidal farm, Jensen wake model and elliptic distribution model are selected for the turbines’ total generating capacity calculation at the maximum speed in the flood tide and ebb tide. Finally, the total generating capacity, regarded as objective function, is calculated in the final simulation, thus the DPSO could guide the individuals to the feasible area and optimal position. The results have been concluded that the optimization algorithm, which increased 6.19% more recourse output than experience method, can be thought as a good tool for engineering design of tidal energy demonstration.

Within real-world marine settings, the operational performance of floating tidal stream turbines is impacted by wave–current interaction effects and platform motion responses. Leveraging the improved delayed detached eddy simulation (IDDES) method, this research constructs a computational fluid dynamics (CFD) numerical analysis framework for floating turbines in wave–current environments. It further investigates the hydrodynamic behaviors and motion response features of the turbine under wave–current interactions. The results show that under the combined action of regular waves and steady currents, the fluctuation amplitudes of the power coefficient and thrust coefficient of the floating turbine exhibit a positive correlation with wave height, whereas the mean values of these coefficients remain relatively stable; in contrast, the mean values of the C_p and C_t are proportional to the wave period. Additionally, the motion amplitude of the platform shows a proportional relationship with both wave height and wave period. Flow field analysis demonstrates that elevations in wave height and period result in enhanced flow turbulence, disrupted wake vortex shedding patterns, non-uniform pressure distributions across the blades, and a larger pressure differential in the blade tip area. Such conditions may potentially induce cavitation erosion and fatigue loads. The results of the research have certain academic significance and value to the development and engineering of floating tidal current energy devices.

In this paper, based on the CFD software ANSYS-Fluent, two-dimensional numerical models are established to investigate the hydrodynamic performance of a self-starting H-Darrius vertical axis tidal turbine (VATT) array of three turbines in a triangular layout with 3D in axial and radial distance. Three main aspects are explored in this study: (1) the self-starting performance, power coefficient, flow fields, and blade force of the double-row VATT array, which are compared with a stand-alone turbine, (2) the wake development of the front and rear displacement turbines, and (3) the feasibility of the double-row self-starting VATT array in practical applications. It is found that the power coefficients of the three turbines in the array all improved compared with that of the stand-alone turbine, and as the load increased, the difference between the averaged power coefficient of the array and a stand-alone turbine was more obvious, with a maximum difference of 3%. The main effects of the front turbines on the rear turbine are energy utilization and turbine vibration. Due to the beam effect between the front turbines, the incident flow rate of the rear turbine increased to approximately 1.2 times the free flow rate. However, the greater rotational fluctuations of the rear turbine mean that although it had a higher power factor, it was more susceptible to fatigue damage. The wake of the rear turbine in the array had a much larger area of influence on both the length and width, but the velocity deficit recovered more quickly to over 95% at a distance of 10D behind it. The rate of wake velocity recovery is load-dependent for a stand-alone self-starting turbine, but this was not evident in the arrays. The positive torque of the turbine is mainly generated when the blade rotates through an azimuth angle from 45° to 160° and mainly benefits from the inner side of the blade. For the double-row three-turbine array, the axial and radial spacing of 3D is reasonable in practical applications.

This article focuses on the optimization of the layout of a tidal current turbine array (TCTA) using the Quantum Discrete Particle Swarm (QDPS) algorithm. The objective of the optimization is to balance the maximum energy output and minimum levelized cost of energy (LCOE). The optimization model proposed in this paper was constructed by combining a computational tidal model and the QDPS algorithm, which incorporate several advancements, including modeling of underwater terrain, obtaining tidal current field using high-fidelity ocean model, considering turbine properties, formulating partial influence of wakes on turbines, accounting for interactions between multiple wakes, modeling of safe operating distance, developing an LCOE model, and computing the sea space utilization area of a tidal farm. The proposed method was applied to optimize the layout of TCTA in a real waterway, which employed maximum tidal current fields during flooding and ebbing periods of spring tides as input for safety reasons. The results indicate that compared to a regular staggered layout, the total power generation improved by 19% and 16%, and the LCOE reduced by 12% and 15%, respectively, when the concluded optimized layout was utilized. Sea area decreased by 24% when LCOE was minimum. Overall, the proposed method has a better performance and can support the set selection as well as turbines placements of tidal current farms.