Tidal Turbine Array Optimization Based on the Discrete Particle Swarm Algorithm

• Published in: China ocean engineering 2018-06, Vol.32 (3), p.358-364
• Main Authors: Wu, Guo-wei, Wu, He, Wang, Xiao-yong, Zhou, Qing-wei, Liu, Xiao-man
• Format: Article
• Language: English
• Subjects: Agricultural economics; Algorithms; Coastal Sciences; Computer simulation; Design engineering; Electric power; Electric power sources; Empirical analysis; Engineering; Farms; Floods; Fluid- and Aerodynamics; Generating capacity; Marine & Freshwater Sciences; Mathematical models; Methods; Numerical and Computational Physics; Objective function; Oceanography; Offshore Engineering; Optimization algorithms; Particle swarm optimization; Simulation; Tidal currents; Tidal energy; Tidal power; Tides; Turbine engines; Turbines
• ISSN: 0890-5487; 2191-8945
• DOI: 10.1007/s13344-018-0037-6

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.