## 4 Research Needs and Trends in Wind Farm Design and Optimization
### Solution Methods  
The general research trend in the solution methods for the generalized WFDO problem is focused on balancing the trade-off between the obtained solution quality and the computational requirements. Hence, the adoption of metaheuristic algorithms in integrated schemes, while employing the concepts of multistep, nesting and hybrid optimization is necessary to tackle the problem. Investigation related to the adequate comparison of solution procedures in realistic wind farm scenarios, and while employing the same state-of-the-art performance metrics and sub-models is required. This is due to the fact that certain comparisons between different solution procedures, that are reported in the literature are meaningless [241, 242], since the adopted performance metrics were different or the amount and type of contrasted algorithms were limited. In addition, the evaluation of other optimization algorithms that have not been used to attempt solve the WFDO problem may provide a wider and more objective perspective about which type of algorithms perform best. Another important aspect to consider is that some solution procedures rely on the relaxation of the complexity of the problem (_i.e._, relaxation of the model or variables complexity). While this may provide interesting conclusions about the mathematical behavior of the problem, relaxations over already simplified models can lead to important inaccuracies, which in turn impact not only the expected wind farm performance but also the solution shape of the problem. Therefore, the proposed solution procedures must tackle the problem without affecting both the mathematical form of the model and the design variables. Many solution procedures, such as the ones based on the Genetic Algorithm, require the discretization of the wind farm site, thus limiting the available locations where WTs can be erected, which in turn impacts the solution quality of the problem as demonstrated in [242, 259]. Although it has been suggested to use irregular, finer and non-uniform discretization grids to improve these limitations [242], the selection of the type, size and refinement of the grid is equally hard as selecting the WT individual locations over a continuous space, thus denoting an important area of improvement for such solution procedures. In addition, most of the optimization procedures reported in the literature have assumed a constant number of WTs or a maximum number of WTs, justified by the assumed limited investment capacity of the wind farm designer. The assumption, however, is very unrealistic, since the financial resources on the worldwide market are very large. In practice, what limits the size of a wind farm (in terms of installed capacity) are practical considerations, such as the maximum amount of energy that can be sold off in an offtake agreement, the limited site space, and very often the transmission capacity. Other approaches, in which the discretization of the wind farm site is considered, have linked the fixed available WT locations with the number of WTs, thus reducing the number of design variables with the implication of restricting the possible wind farm layouts and thus the solution quality of the problem, as previously discussed. The determination of the optimal number of WTs, assuming no predefined investment capacity or any linkage to the process of domain discretization, is complex and the best procedures perform a sensitivity analysis to determine its optimum value. However, sensitivity analyses may require long computation times and will depend on the effectiveness of the solution procedure to find optimal or near-optimal solutions for scenarios having different predefined number of WTs. It should be noted that optimized wind farm layouts having different amount of WTs can be significantly different, thus hindering the determination of the optimal number of WTs based on solutions to scenarios having different number of WTs. In this regard, the development of adaptive algorithms that include the number of WTs as a design variable is required.