Status: a revised version of this preprint is currently under review for the journal WES.
Offshore and onshore ground-generation airborne wind energy
power curve characterization
Markus Sommerfeld1,Martin Dörenkämper2,Jochem De Schutter3,and Curran Crawford1Markus Sommerfeld et al.Markus Sommerfeld1,Martin Dörenkämper2,Jochem De Schutter3,and Curran Crawford1
Received: 13 Nov 2020 – Discussion started: 19 Nov 2020
Abstract. Airborne wind energy systems (AWESs) aim to operate at altitudes well above conventional wind turbines (WTs) and harvest energy from stronger winds aloft. While multiple AWES concepts compete for entry into the market, this study focuses on ground-generation AWES. Various companies and researchers proposed power curve characterizations for AWES, but no consensus for an industry-wide standard has been reached. An universal description of a ground-generation AWES power curve is difficult to define because of complex tether and drag losses as well as alternating flight paths over changing wind conditions with altitude, as compared to conventional WT with winds at fixed hub height and rotor area normalization. Therefore, this study determines AWES power and annual energy prediction (AEP) based on the awenox optimal control model for two AWES sizes, driven by representative 10-minute onshore and offshore mesoscale WRF wind data. The wind resource is analyzed with respect to atmospheric stability as well as annual and diurnal variation. The wind data is categorized using k-means clustering, to reduce the computational cost. The impact of changing wind conditions on AWES trajectory and power cycle is investigated. Optimal operating heights are below 400 m onshore and below 200 m offshore. Efforts are made to derive AWES power coefficients similar to conventional WT to enable a simple power and AEP estimation for a given site and system. This AWES power coefficient decreases up to rated power due to the increasing tether length with wind speed and the accompanying tether losses. A comparison between different AEP estimation methods shows that a low number of clusters with three representative wind profiles within the clusters yields the highest AEP, as other wind models average out high wind speeds which are responsible for a high percentage of the overall AEP.
This research describes the optimal ground-generation airborne wind energy system power and representative for two system sizes. The flight trajectory is subject to representative, simulated onshore and offshore wind data. Wind conditions up to 1000 m are analyzed with respect to wind profile shape, atmospheric stability as well as annual and diurnal variation. Performance is compared to that of conventional wind turbines.
This research describes the optimal ground-generation airborne wind energy system power and...