  A novel approach for the solution of the wind farm layout optimization
problem is presented. The annual energy production is maximized with
constraints on the minimum and maximum number of wind turbines placed, and on
the minimum spacing between the wind turbines. The proposed approach relies on
a density-based topology optimization method, where continuous density
variables varying between zero and one are assigned to each potential wind
turbine location. A wind turbine exists if its associated variable equals one,
otherwise it does not exist if the associated variable is zero. Intermediate
values of the density variables are penalized with interpolation schemes
traditionally used in the context of multi-material structural topology
optimization. The penalized intermediate values of the design variables become
uneconomical and the optimization algorithm is implicitly pushed towards a
preference of crisp 0-1 final values. The optimization problem is solved with a
gradient-based algorithm based on first-order information. Because of the
proposed problem formulation, the functions involved are formulated explicitly
in terms of the design variables and their analytical gradients can be
calculated directly. The numerical results highlight the capability of the
proposed approach in finding far from intuitive wind farm layouts with small
computational resources and time.
