Sustainable wind farm layout design for maximizing power output and reducing environmental impact

Wind farm layout design continues to face methodological constraints that limit its applicability under realistic operating conditions. Existing approaches frequently rely on single-objective formulations that prioritize either energy maximization or wake-loss reduction, thereby failing to capture the interdependent trade-offs among power generation, turbulence intensity, and wake-induced performance degradation. In addition, widely adopted wake models often use simplified aerodynamic representations that overlook turbine–turbine coupling effects, while deterministic wind-field assumptions ignore the stochastic variability in wind speed and direction that critically influences wake propagation. These limitations underscore the need for a more comprehensive and physically grounded optimization strategy. This study proposes a tailored multi-objective optimization framework that integrates analytical wake modeling with stochastic environmental characterization to identify efficient turbine placements within the farm boundary. The method concurrently optimizes power output, turbulence attenuation, and wake-related energy deficits while enforcing spatial and operational constraints. Numerical evaluations demonstrate marked performance improvements relative to baseline configurations. Turbines situated in favorable aerodynamic regions (T4 and T5) achieve power outputs of 1.84–1.89 MW, representing an increase of up to 72% compared to downstream turbines subjected to wake interference (1.03–1.13 MW). Turbulence intensity decreases by more than 55% (1.20–1.28 versus 2.58–2.81), and wake-related energy losses are reduced by over 60% (0.0065–0.0072 versus 0.013–0.017). These quantitative gains confirm the efficacy of the proposed optimization framework and highlight its potential for scalability, enhanced aerodynamic fidelity, and integration into future large-scale wind-farm planning and operational decision-support systems.