An assessment of the mesoscale to microscale influences on wind turbine energy performance at a peri-urban coastal location from the Irish wind atlas and onsite LiDAR measurements

• Published in: Sustainable energy technologies and assessments Vol. 36; p. 100537
• Main Authors: Byrne, Raymond, Hewitt, Neil J., Griffiths, Philip, MacArtain, Paul
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2019
• Subjects: Distributed wind; Electrical energy rose; LiDAR; Wind atlas; Wind resource; CFD; Distributed wind; a.s.l; DM; Electrical energy rose; WRF; WPD; Wind atlas; Wind resource; ECMWF; SEAI; WT; JMA; SCADA; NASA; NWP; LiDAR; AEP; WAsP; LOS; DkIT; EER; a.g.l; ERA; WED; MetUM; NECEP
• ISSN: 2213-1388
• DOI: 10.1016/j.seta.2019.100537

•Dundalk bay enhances coastal site wind potential by the steering of offshore winds.•Annual energy prediction from Irish wind atlas is within 3% of measured output.•Building heights down to 20% of 60 m (WT hub height), within 1 km, are influential.•Directional energy gains up to 134% or losses up to 59% due to building influences.•Measured wind shear profiles in peri-urban areas are highly variable. As the global wind energy industry advances to larger wind turbine systems, there still remains opportunities for deploying single medium-to-large-scale wind turbines in distributed wind energy applications. These include community wind farms and “behind-the-meter” wind applications. Such sites tend to be closer to population centres at lower elevations that have more complex wind regimes due to surrounding orography, local terrain and obstacles such as buildings. This research case study examines the regional mesoscale influences and local microscale influences on the post construction measured energy performance of an 850 kW rated wind turbine, with a 60 m hub height, at a peri-urban coastal location. The remodelled Irish wind atlas is used to characterise mesoscale and microscale influences on wind resource around the wind turbine site. A directional analysis of modelled predicted annual energy is compared to the measured wind turbine electrical energy rose. Data from a nine month LiDAR measurement campaign is used to assess directional wind shear profiles at the site. The shear profiles are examined with respect to local buildings obstacles to gain insights into the microscale sources of discrepancies between the predicted energy from the wind atlas and actual energy output of the wind turbine.