## 2 Overview of the Basic Concepts of Wind Farm Design and Optimization
### Visual Impact
#### Uncertainty and Risk Management  
The uncertainty associated to a process can be defined as a state of limited knowledge, in which it is not possible to describe with accuracy and/or precision the actual state and/or a future state and its outcome(s), if any. Uncertainty can be cataloged as epistemic, when a lack-of-knowledge on the process exists, or as random, when parameters vary stochastically during the process development. The metric used to measure uncertainty is the possible deviation in the prediction of the actual and/or future events based on the actual knowledge of the process. The risk of a process, therefore, can be defined as a state of uncertainty where the possible outcomes are undesired. Uncertainties associated to the planning process of wind farms can be decomposed in three main tracks:  
(1) _Uncertainty related to the wind resource estimation_. Uncertainties in wind resource are divided in four general categories [133]: (1) uncertainty due to the measurement processes; (2) uncertainty in the short- and long-term variations of atmospheric variables; (3) uncertainty due to wind resource variability; and (4) uncertainty due site assessment. The large-scale atmospheric effects and the long-term variation of atmospheric variables imposes the major challenge [134,135], as they are considered to be the largest sources of uncertainty during the micro-scale wind resource estimation. The certainty and quality of the measured wind resource is crucial during: (1) spatial wind mapping and during (2) WT wake-based power losses quantification [136], both inducing additional uncertainty due to their modeling assumptions, inaccuracies and limitations (e.g., the induced uncertainty related to the limited resolution of topographic and roughness maps, wind direction uncertainty, flow modeling limitations, _etc._[106]). The objective of the wind farm designer is to increase the accuracy and precision of both the measurements and predictions of atmospheric variables values in space and time. (2) _Uncertainty related to the WT technology_. Uncertainties in WT performance may be divided in three: those related to (1) the WT manufacturing process; (2) the WT power conversion model (e.g., the power output as a function of atmospheric variables and other undesirable effects such as wakes, WT blade soiling and degradation and mechanical/electrical losses among others); and (3) those related to the WT technical availability (e.g., O&M scheduling). The objective of the WT designer is to reduce the performance deviations from the theoretical expectations of the constituent mechanical and electrical systems of a WT. (3) _Uncertainty related to economic prospections_. The objective of the wind farm designer is to increase the accuracy and precision of the profitability projections of the project accounting for the evolution of the energy prices as well as all relevant variable costs (O&M, WT degradation, civil work, decommissioning, _etc._). All uncertainty tracks are related and each one depends on the previous one as naturally listed before. Therefore, the total economic prospection uncertainty might be high if no proper uncertainty mitigation processes are performed, thus affecting the final potential funding decisions of financial institutions. To improve the economic prospection certainty, the wind farm designer must follow existing guidelines and standards to mitigate uncertainty at all levels. Some examples include, but are not limited to:  
* IEC 61400-12, Annexes D, E, F, G, I, J and K [29]. Anemometry, calibration procedures, meteorological mast geometry and induced flow affectation. * Wind Turbine Design Cost and Scaling Model from the National Renewable Energy Laboratory (NREL) [137].