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Wind energy plays a vital role in supporting decarbonization efforts in the energy sector. As a result, the design and operation of wind farms have been extensively explored. Previous studies have primarily focused on turbine layout optimization, assessing wake deficits, power output, and the levelized cost of energy. In contrast, limited research has been dedicated to a combined spatial and economic assessment that considers existing transmission grids. This study proposes a holistic, spatially explicit metaheuristic approach that iteratively optimizes turbine placement and integrates resulting wind farms into existing grids using Dijkstra’s algorithm. The outputs include annual energy yield and grid connection costs. Liezen, a district in Austria with approximately 2,000 km2 of feasible area for wind farm development, serves as the case study. Results show that variation in turbine spacing can reduce connection costs by an average of up to 45%, while energy yield losses remain relatively modest at 25%.