Abstract

Optimized wind turbine configurations enable sustainable power generation; however, maximizing total power output through wind farm layout optimization (WFLO) remains a critical and complex challenge. WFLO strategically identifies the optimal positioning of the wind turbines within a designated wind farm area to mitigate wake effects and maximize overall power output. Wake effects, where upstream turbines diminish the wind velocity reaching downstream turbines, can substantially lower the overall power output of a wind farm. This study proposes an ant colony optimization (ACO) approach to address WFLO, employing a continuous wind farm model that enables flexible turbine placement to minimize the cost of energy (CoE). Three scenarios were examined: constant wind speed in a single wind direction; constant wind speed in multiple wind directions; and a variable wind speed in multiple directions incorporating direction-specific occurrence probabilities. The proposed framework facilitates continuous spatial optimization, substantially expanding the feasible search space by eliminating grid-based constraints. Its effectiveness was validated through comparative evaluation against methods reported in prior studies. The results demonstrate that the ACO algorithm consistently achieves superior performance, yielding a 2.13–4.03% reduction in CoE and a 2.22–4.06% increase in total power output across diverse wind conditions. This study highlights the potential of continuous spatial optimization as an effective alternative to conventional grid-based approaches in WFLO.

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