Abstract. Wind Farm Layout Optimization Problem?(WFLOP) is a critical issuewhen installing a large wind farm. Many studies have focused on the WFLOPbut only for a limited number of turbines and idealized wind speeddistributions. In this study, we apply the Genetic Algorithm?(GA) to solvethe WFLOP for large hypothetical offshore wind farms using real wind data.GA mimics the natural selection process observed in nature, which is thesurvival of the fittest. The study site is the Palk Strait, located betweenIndia and Sri Lanka. This site is a potential hotspot of offshore wind inIndia. A modified Jensen wake model is used to calculate the wake losses. GA?is used to produce optimal layouts for four different wind farms at thespecified site. We use two different optimization approaches: one where thenumber of turbines is kept the same as the thumb rule layout and anotherwhere the number of turbines is allowed to vary. The results show thatlayout optimization leads to large improvements in power generation (up to28 %), efficiency (up to 34 %), and cost (up to 25 %) compared to thethumb rule due to the reduction in wake losses. Optimized layouts where both the number and locations of turbines are allowed to vary produce better results in terms of efficiency and cost but also leads to lower installed capacity and power generation. Wind energy is growing at an unprecedented rate in India. Easily accessible terrestrial wind resources are almost saturated, and offshore wind is the new frontier. This study can play an important role while taking the first steps towards the expansion of offshore wind in India.
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