Real-Time Optimization and Adaptation of the Crosswind Flight of Tethered Wings for Airborne Wind Energy

Airborne wind energy systems aim to generate renewable energy by means of the aerodynamic lift produced using a wing tethered to the ground and controlled to fly crosswind paths. The problem of maximizing the average power developed by the generator, in the presence of limited information on wind speed and direction, is considered. At constant tether speed operation, the power is related to the traction force generated by the wing. First, a study of the traction force is presented for a general path parametrization. In particular, the sensitivity of the traction force on the path parameters is analyzed. Then, the results of this analysis are exploited to design an algorithm to maximize the force, hence the power, in real-time. The algorithm uses only the measured traction force on the tether and the wing's position, and it is able to adapt the system's operation to maximize the average force with uncertain and time-varying wind. The influence of inaccurate sensor readings and turbulent wind are also discussed. The presented algorithm is not dependent on a specific hardware setup and can act as an extension of existing control structures. Both numerical simulations and experimental results are presented to highlight the effectiveness of the approach.

[1]  Ilya V. Kolmanovsky,et al.  Modeling and control design for a prototype lighter-than-air wind energy system , 2012, 2012 American Control Conference (ACC).

[2]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[3]  John L. Nazareth,et al.  Introduction to derivative-free optimization , 2010, Math. Comput..

[4]  Wubbo Johannes Ockels,et al.  Tracking control with adaption of kites , 2010, ArXiv.

[5]  M. L. Loyd Crosswind kite power , 1980 .

[6]  Lorenzo Fagiano,et al.  Power Kites for Wind Energy Generation [Applications of Control] , 2007, IEEE Control Systems.

[7]  Moritz Diehl,et al.  Nonlinear MPC of kites under varying wind conditions for a new class of large‐scale wind power generators , 2007 .

[8]  Dominique Bonvin,et al.  Real-Time Optimization for Kites , 2013, PSYCO.

[9]  M. L. Loyd,et al.  Crosswind kite power (for large-scale wind power production) , 1980 .

[10]  Lorenzo Fagiano,et al.  Power kites for wind energy generation , 2007 .

[11]  Rui Huang,et al.  Nonlinear Model Predictive Control and Dynamic Real Time Optimization for Large-scale Processes , 2010 .

[12]  Lorenzo Fagiano,et al.  Airborne Wind Energy: An overview , 2012, 2012 American Control Conference (ACC).

[13]  Lorenzo Fagiano,et al.  On Sensor Fusion for Airborne Wind Energy Systems , 2012, IEEE Transactions on Control Systems Technology.

[14]  Lorenzo Fagiano,et al.  Automatic Crosswind Flight of Tethered Wings for Airborne Wind Energy: Modeling, Control Design, and Experimental Results , 2013, IEEE Transactions on Control Systems Technology.

[15]  Dario Piga,et al.  Optimization of airborne wind energy generators , 2012 .

[16]  Sanket Sanjay Diwale Optimal control for power generating kites , 2014 .

[17]  Lorenzo Fagiano,et al.  High Altitude Wind Energy Generation Using Controlled Power Kites , 2010, IEEE Transactions on Control Systems Technology.

[18]  P. Williams,et al.  Optimal Cross-Wind Towing and Power Generation with Tethered Kites , 2007 .

[19]  Moritz Diehl,et al.  Optimal control for power generating kites , 2007, 2007 European Control Conference (ECC).

[20]  Roland Schmehl,et al.  Flight Dynamics and Stability of a Tethered Inflatable Kiteplane , 2011 .

[21]  Lorenzo Mario Fagiano,et al.  Control of Tethered Airfoils for High-Altitude Wind Energy Generation - Advanced control methods as key technologies for a breakthrough in renewable energy generation [Doctoral dissertation - Ph.D. in Information and System Engineering - Ciclo XXI - Politecnico di Torino] , 2009 .

[22]  Lorenzo Fagiano,et al.  Design of a Small-Scale Prototype for Research in Airborne Wind Energy , 2013, IEEE/ASME Transactions on Mechatronics.