A comparison of four microscale wind flow models in predicting the real-world performance of a large-scale peri-urban wind turbine, using onsite LiDAR wind measurements. (August 2021)

• Record Type: Journal Article
• Authors: Byrne, Raymond; Hewitt, Neil J.; Griffiths, Philip; MacArtain, Paul
• Is Part Of: Sustainable energy technologies and assessments. Volume 46(2021)
• Publication Date: 2021-08
• Subjects: AEP Annual Energy Production -- a.g.l. Above ground level -- a.s.l. Above sea level -- CFD Computational Fluid Dynamics -- CL Canopy Layer -- DkIT Dundalk Institute of Technology -- EER Electrical Energy Rose -- GCV General Collocated Velocity Method -- IEA International Energy Agency -- IEC International Electrotechnical Commission -- ISL Inertial Sublayer -- LiD LiDAR Location -- LiDAR Light Detection and Ranging -- M Met Mast Location -- RANS Reynolds averaged Navier-Stokes RANS -- RSL Roughness Sublayer -- SCADA Supervisory Control and Data Acquisition -- SEAI Sustainable Energy Authority of Ireland -- SRTM Shuttle Radar Topography Mission -- UTM Universal Transverse Mercator -- WAsP Wind Atlas Applications Program -- WGS World Geodetic System -- WPD Wind Power Density -- WT Wind Turbine Location; Distributed wind -- Wind resource -- Micro-siting -- LiDAR -- Flow models; Renewable energy sources -- Periodicals; Energy development -- Technological innovations -- Periodicals; Electric power production -- Periodicals; Energy storage -- Periodicals; 333.79
• DOI: 10.1016/j.seta.2021.101323
• Languages: English
• ISSNs: 2213-1388

Abstract

Highlights: Model energy predictions vary by 1.4–64% compared with actual performance. Obstacles best represented as roughness elements or as mesh blocking elements. Low-rise buildings, 20% of turbine hub height and above have an impact. Obstacles up to a distance of 100 obstacle heights should be considered. Models perform better upscaling measurements from 3 times the obstacle heights. Abstract: As wind energy continues to expand, new markets for distributed wind applications are expected, including behind-the-meter deployment at industrial consumer sites in peri-urban areas. The presence of buildings in these areas can give rise to complex wind regimes. This study compares the measured annual energy output of an operating Vestas V52 wind turbine, in a peri-urban environment, with predictions from four microscale wind flow models. The models upscale and downscale onsite LiDAR wind measurements at six heights from 10 m to 200 m. The models consist of a linear shelter model and three RANS CFD approaches, implemented in two widely used micro-siting tools, namely WAsP and WindSim. Variations from 1.4% to 64% between model predicted and measured electrical energy output are observed. For low-rise buildings with heights up to 20% of the turbine hub height, the models are most accurate using wind measurements at ~ 3 times the height of the buildings. In the case of a tall narrow building, ~ 80% of the hub height, best model predictions are from twice the height of the building. Wind shear measurements suggest that obstacles down to 20% of the hub height, up to distances of 100 obstacles heights away, are significant.