Coupled Kite-Ground Station Simulink Model for Optimal Flight Path Following Assessment

Frédéric Bourgault Principal Scientist New Leaf Management Ltd.

1177 West Hastings Street, Suite 500 Vancouver, BC V6E 2K3 Canada frederic@newleaf.co www.newleaf.co

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Coupled Kite-Ground Station Simulink Model for Optimal Flight

Path Following Assessment

Andreas Klein Miloslavich1_{, Markus Sommerfeld}1_{, Frédéric Bourgault}2_{, Curran Crawford}1_{, Mojtaba Kheiri}2,3 1_{University of Victoria,}2_{New Leaf Management Ltd.,}3_{Concordia University}

Crosswind Kite Power Systems (CKPSs), a specific type of airborne wind energy systems, will operate at higher al-titudes than conventional wind turbines. CKPSs will fly through a significant portion of the atmospheric bound-ary layer, and therefore encounter a wide range of inci-dent wind profiles corresponding to wide ranging atmo-spheric stability conditions resulting from synoptic and diurnal weather conditions. This study aims to demon-strate an approach to considering realistic wind speed profiles for a lift mode (a.k.a. pumping mode) CKPS. The focus is on a time-domain simulation of tethered flight to follow optimal trajectories solved for both simple and re-alistic wind speed profiles. The pre-computed trajecto-ries may not be optimal, or even achievable, when con-sidering forward-marching flight dynamics compared to the necessarily simplified optimization flight model. In particular, ground-station tether reel-in/out speed and torque envelopes and control directly affect the power harvesting performance, longevity and robustness of the system. An approach is being developed to support ground station control coupled with tether and flight dy-namics, to explore controller synthesis solutions that do not excite the coupled kiteśtetherśground-station system dynamics, especially during transitions between harvest-ing and retraction flight phases.

In the proposed approach, the wind speed profiles from the mesoscale Weather Research and Forecasting (WRF) model [1] are first implemented in the open source AWE-box [2] which is then used to determine optimal flight paths for a range of wind profiles. A flight controller is

im-plemented in a Matlab’s Simulink model to follow the pre-computed optimal trajectories generated with the AWE-box in a time-marching dynamic simulation. Dynamic tether tension, structural loads and energy harvesting performance are estimated and compared with the of-fline, idealized control actions obtained with AWEbox. The ultimate goal is to integrate both the base-station and flight controllers in the combined system dynamic model in Simulink, assess the ability and robustness of the con-trol system to follow those optimal paths, and evaluate the differences between optimal idealized performance and that achievable dynamically in the presence of wind disturbances. This evaluation will also form the basis for assessing lifetime structural fatigue loads and sizing re-quirements.

Sample dynamic simulation trajectory result compared to optimal reference trajectory generated with AWEbox in wind field in x-direction with log profile starting at 8 m/s for zref= 10 m with exponent α = 1/7, and winch at (0,0,0).

References:

[1] Skamarock,C. et al.: A Description of the Advanced Research WRF Version 3.(2008)

[2] De Schutter, J. et al.: Python toolbox for modelling and op-timal control of multiple-kite systems for Airborne Wind Energy. https://github.com/awebox/awebox