Mahdi Khorasanchi - Assistant Professor, School of Mechanical Engineering, Sharif University of Technology
Hassan Sayyaadi - Professor, School of Mechanical Engineering, Sharif University of Technology
Pegah Ziyaei - M.Sc. Student, School of Mechanical Engineering, Sharif University of Technology
Ali Sadollah - Postdoctoral, School of Mechanical Engineering, Sharif University of Technology

The minimum cost of energy is the goal of wind farm layout optimization. This can be achieved by maximizing the total energy and minimizing the total costs of the farm. This study considered two sizes of commercial turbines and thus we modified the simple cost model proposed by Mosetti et al. [1], using cost scaling law. We also used Jensen wake model to calculate the total output power of the wind farm in three different wind scenarios and considered the effect of the wind speed on the performance and thrust coefficients. By using Genetic Algorithm, we first practiced previous studies to validate our model. In each scenario, the layout with the minimum cost of energy is reported as optimized layout. It was observed that the variation of performance and thrust coefficients with wind speed, reduced the total power and thus increased the cost of energy. Next, two scenarios were investigated, i.e. (1) a farm populated with only smaller size turbines and (2) a farm with a random mixture of small and large turbines. The layouts of both scenarios were optimized. The larger turbines only remained in the optimum layout of the second scenario and reduced the cost of energy into half of the first scenario.

offshore wind farm, layout optimization, GA, performance coefficient, non-homogenous, turbines size