Posters

Abstract

Wind farm layout optimization is usually subjected to boundary constraints of irregular shapes, whose analytical expressions are rarely available. A new methodology to integrate multiple, disconnected and irregular domain boundaries in wind farm layout optimization problems is presented. The method relies on the analytical gradients of the distances between wind turbine locations and boundaries, which are represented by polygons. This allows for a continuous optimization formulation, which is generally less costly than the discrete counterpart. A limitation of the method if combined with gradient-based solvers is that each wind turbine is placed within the nearest polygon when the optimization is started in order to satisfy the boundary constraints, thus the turbine allocation per polygon is highly dependent on the initial guess. To overcome this, two independent strategies are proposed. A study case is presented to demonstrate the applicability of the method and the proposed strategies. A wind farm layout is optimized in order to maximize the AEP in a non-uniform wind resource site. The problem is constrained by the minimum distance between turbines and five irregular inclusion zones. Initial guesses are used to solve the problem following three independent approaches: (1) a baseline approach that uses a gradient-based solver; (2) its combination with the relaxation of boundaries, allowing for a better design space exploration, and; (3) the application of a heuristic algorithm prior to the gradient-based optimization, improving the allocation of wind turbines within the inclusion polygons based on the potential wind resource and the available area. The results show that the relaxation of boundaries combined with a gradient-based solver achieves on average +10.2% of AEP with respect to the baseline, whilst the heuristic algorithm combined with a gradient-based solver achieves on average +22.2% of AEP with respect to the baseline.