Wind resource assessment using airborne LiDAR data and smoothed particle hydrodynamics. (September 2017)

• Record Type: Journal Article
• Authors: Lukač, Niko; Štumberger, Gorazd; Žalik, Borut
• Is Part Of: Environmental modelling & software. Volume 95(2017)
• Page Start: 1
• Page End: 12
• Publication Date: 2017-09
• Subjects: Wind simulation -- Wind resource assessment -- LiDAR data -- Aerodynamic roughness length -- Typical meteorological year -- Smoothed particle hydrodynamics; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.05.006
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The increasing availability of airborne Light Detection And Ranging (LiDAR) data provides new opportunities for environmental simulations. This paper proposes a new method for wind resource assessment by using wind simulation over 3D geometry extracted from classified LiDAR data. The simulation of wind flow is performed by using Smoothed Particle Hydrodynamics (SPH) in two phases for each time-step, firstly over low-resolution Digital Elevation Model (DEM) data, and secondly over high-resolution LiDAR data. Inlet wind particles depend on the logarithmic wind profile, where the morphometric aerodynamic roughness length is considered. The estimated wind power is integrated over a given timespan, resulting in wind energy potential. The simulated velocities were validated with annual measurements, where an agreement of 80.72% and 90.81% was achieved for ~ 0 . 5 k m 2 sized urban and rural areas, respectively. The cumulative wind energy potential at 20 m above surface height is at 7.62 GWh and 56.613 GWh for the given areas, respectively. Highlights: Novel wind resource assessment method based on two-phase wind simulation with SPH. Classified LiDAR data is used for geometry and morphometrically estimated roughness. The method had an agreement of 80.72% and 90.81% with measurements at two areas. The method outperformed analytical Wind Atlas in comparison to measurements. Suitable for wind power systems' placement in urban and rural areas.