Wind farm layout optimization in complex terrain based on CFD and IGA-PSO

Weicheng Hu, Qingshan Yang, Ziting Yuan and Fucheng Yang

Energy, 2024, vol. 288, issue C

Abstract: A novel hybrid method is proposed for wind farm layout optimization in complex terrain. Firstly, an elliptical modeling method is presented with the Witoszynski-shaped transition curve in the computational fluid dynamics (CFD) simulations. Wind resources in complex terrain are estimated by combining CFD simulations with measured wind data, and an inverse distance weighting method is introduced. Then, an improved genetic algorithm (IGA) is presented to optimize the wind farm layout, which can significantly improve efficiency and avoid falling into local optima. Finally, to overcome the grid limitation of IGA, a particle swarm optimization (PSO) method is introduced for further optimization, i.e., IGA-PSO. The proposed method is used to optimize the wind farm layout in the complex terrain of Qianjiang, China. Various wake models and cost models are considered in the optimization, where wake models include Jensen, Gaussian wake model (GWM), double Gaussian wake model (DGWM) and cost models include annual energy production (AEP) and net annual value (NAV). The results show that the proposed method outperforms other three algorithms in providing a more favorable wind farm layout in complex terrain.

Keywords: Wind farm; Layout optimization; Complex terrain; Computational fluid dynamics; Improved genetic algorithm; Particle swarm optimization (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:288:y:2024:i:c:s0360544223031390

DOI: 10.1016/j.energy.2023.129745

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