Boosting wind farm productivity: smart turbine placement with cutting-edge AI algorithms

Abstract

Efficient wind farm development necessitates careful planning of wind turbine placement. The primary aim of this optimization process is to strategically position turbines to minimize the wake effect. The ongoing study seeks to standardize wake losses across all turbines in the wind farm through the adoption of a novel diagonal layout. To achieve this objective, an objective function has been devised and employed by a genetic algorithm, aiming to maximize the energy production of the farm while avoiding the concentration of wake on specific turbines. This methodology was applied to the Gasiri wind farm using simulation. The results of the optimization show great promise, indicating a potential energy increase of 17% following the implementation of the optimized layout. Furthermore, the study highlights that the new turbine placements, characterized by higher nominal power, are more favorably aligned forward, in accordance with the wind direction, compared to their original positions. Additionally, a substantial reduction in the mechanical fatigue of the turbine blades was noted.