A Computational Fluid Dynamics Approach for Wind Farm Location Mapping Based on Digital Elevation Model Yoga Satria Putra-1,*, Evi Noviani-2, Asri Rahmawati-2, Elsa Kurnia-1, Maria Citra Puella Christy-1, Sabila Zhafarina-1, Sinta-1, Umi Aisyah-1, Halaida Zahara-1, Rendi-1, Sy. Lexsi Firnanda-1
1-Geophysics Study Program, Faculty of Mathematics and Natural Sciences, Tanjungpura University,
Pontianak, West Kalimantan,
2-Mathematics Study Program, Faculty of Mathematics and Natural Sciences, Tanjungpura University, Pontianak, West Kalimantan
Abstract
Accurate wind distribution modeling is crucial for effective wind farm planning, particularly in regions with diverse topographic characteristics. This study aims to evaluate the performance of the Computational Fluid Dynamics (CFD) method in simulating wind flow over two types of terrain, flat and hilly, as an initial step toward its broader application in complex terrains. The approach integrates wind speed data with a Digital Elevation Model (DEM) derived from the Shuttle Radar Topography Mission (SRTM), with a spatial resolution of 30 meters. Two case studies were selected: Leipzig, Germany (flat terrain) and Askervein Hill, Scotland (hilly terrain), as both are internationally recognized test sites with well-documented wind observation data. These locations were chosen to validate the accuracy of the CFD model before applying it to complex regions in Indonesia, where direct wind measurements are limited. The simulation results demonstrate that CFD is capable of capturing spatial variations in wind speed and identifying zones of wind acceleration influenced by terrain morphology. Validation with observational data shows good agreement, especially at the hilltops and windward slopes. While SRTM data is sufficiently representative for regional-scale analysis, its resolution limitations can affect accuracy in steep terrain. Future improvements to DEM resolution may involve higher-resolution topographic data, such as DEMNAS or LiDAR-based elevation models, to improve wind flow modeling in complex environments.
