Wind power production and use are very environmentally friendly. A report by the U.S. Energy Department suggests that the U.S. has a potential of avoiding the emission of 12.3 gigatonnes of greenhouse gasses and 260 billion gallons of water by 2050. This can be achieved by increasing the reliance on wind energy to power schools, businesses, and homes. However, reliance on wind power is dependent upon the viability of the productions methods (Pardalos, 2013). Hence, to reap from economies of scale the wind farms have grown larger, the turbines have also become larger with smarter controls and capabilities that are more advanced. However, as efforts are made to reduce costs another problem arises, and that is the wake effects produced by grouped turbines that reduce the power produced (Pardalos, 2013). It, therefore, becomes necessary to find methods to reduce the wake effect and hence maximizing production; the Wind Farm Layout Optimization Problem (WFLOP) does just that. It involves positioning the turbines in such a way as to minimize wake effects and hence maximize power production (Feng & Shen, 2015).Grouping turbines not only jeopardize the operation of rotors and affect the life expectancy of turbines, it also leads to a decrease in the power produced due to the presence of wake effects within the wind farm (Chowdhury et al., 2010). When a turbine is running, it generates a ‘‘wake’’ of turbulence that propagates downwind. This wake causes the wind speed and, therefore, the power extracted by the turbines to reduce. Levels of wake interference can differ depending on the relative locations of the wind turbines and wind direction. Effects of wakes are more considerable in large wind farms, and hence it becomes imperative to minimize them and maximize energy production.
Currently, the WFLO problem is solved by employing simple rules that point to a rectilinear layout; it involves organizing the turbines in straight rows giving a conveniently large distance between each turbine (Pardalos, 2013). However, recent research has shown that an irregular arrangement has a higher expected production compared to the rectilinear layout. On this regard, mathematical optimization algorithms have been developed to calculate the most suitable wind farm layout (Feng & Shen, 2015). The problem has been receiving a lot of attention in recent times; however, there is still more to be done to guarantee minimal costs and maximum energy production.