Abstract
This article focuses on the optimization of marine hydrokinetic farms of coaxial dual-rotor turbines with wake interaction. To perform the optimization, we introduce a new analytical wake model for this turbine configuration and validate it herein. The proposed model predicts the wake velocity deficit in the near- and far-wake of the turbine in terms of the diameters and axial induction factors of the upstream and downstream rotors and the location of the near-wake boundary. It is derived by utilizing mass- and momentum balancing in the near- and far-wake control volumes, supplemented by the application of Bernoulli's principle along pertinent streamlines. The analytical prediction is compared with computational simulation results for different flow conditions to find good agreement between them. The optimization problem is solved by the implementation of a genetic algorithm, which is developed based on the wake model. The algorithm maximizes farm efficiency by minimizing the wake interactions among the turbines. The influence of different parameters of the algorithm on its overall performance and efficiency is investigated to discover that a perfect integration among the parameters is essential for a successful search. Eventually, three different cases are studied with different farm sizes, numbers of cells in farm layouts, and aspect ratios of the farm at each of the flow conditions to illustrate the functionality and robustness of the algorithm that is based on the proposed wake model. The optimization results will be useful for the assessment of the hydrokinetic power potential of such turbine configurations in an ocean or riverine current.