A lagrangian flight simulator for airborne wind energy systems

Journal Article (2019)
Author(s)

Gonzalo Sánchez-Arriaga (Carlos III University of Madrid)

Alejandro Pastor-Rodríguez (Carlos III University of Madrid)

Manuel Sanjurjo-Rivo (Carlos III University of Madrid)

Roland Schmehl (TU Delft - Wind Energy)

Research Group
Wind Energy
Copyright
© 2019 Gonzalo Sánchez-Arriaga, Alejandro Pastor-Rodríguez, Manuel Sanjurjo-Rivo, R. Schmehl
DOI related publication
https://doi.org/10.1016/j.apm.2018.12.016
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Gonzalo Sánchez-Arriaga, Alejandro Pastor-Rodríguez, Manuel Sanjurjo-Rivo, R. Schmehl
Research Group
Wind Energy
Volume number
69
Pages (from-to)
665-684
Reuse Rights

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Abstract

A parallelized flight simulator for the dynamic analysis of airborne wind energy (AWE) systems for ground- and fly-generation configurations is presented. The mechanical system comprises a kite or fixed-wing drone equipped with rotors and linked to the ground by a flexible tether. The time-dependent control vector of the simulator mimics real AWE systems and it includes the length of the main tether, the geometry of the bridle, the torque of the motor controllers of the rotors, and the deflections of ailerons, rudder and elevator. The use of a lagrangian formulation with a minimal coordinate approach and discretizing the main tether as a chain of inelastic straight rods linked by ideal (dissipative-less) rotational joints, yielded a non-stiff set of ordinary differential equations free of algebraic constraints. Several verification tests, including a reel-in maneuver that admits an analytical solution, are presented. The efficiency of the parallelization with the number of tether segments, and trade-off analysis of the lagrangian and hamiltonian formulations are also considered. The versatility of the simulator is highlighted by analyzing two maneuvers that are relevant for AWE scenarios. First, the simulator is used to compute periodic figure-of-eight trajectories with an open-loop control law that varies the geometry of the kite’s bridle, as frequently done in ground-generation AWE systems. Second, an unstable equilibrium state of a tethered drone equipped with two rotors for energy harvesting is stabilized by implementing a closed-loop control strategy for the deflection of the control aerodynamic surfaces.

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