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Pumping airborne wind energy (AWE) systems employ a kite to convert wind energy into electricity, through a cyclic reeling motion of the tether. The problem of computing the optimal reeling speed for the sake of maximizing the average cycle power is considered. The difficulty stems from two aspects: 1) the uncertain, time- (and space-) varying nature of wind speed, which can not be measured accurately, and 2) the need to consider, in the same optimization problem, the different operational phases of the power cycle. A new, model-based approach that solves this problem is proposed. In the design phase, a model of the AWE system is employed to collect data pertaining to the cycle power obtained with various reel-in/reel-out speed pairs, assuming known wind speed. Then, a nonlinear map, identified from these data, is used as cost function in an optimization program that computes the best reel-in and -out speed pairs for each wind speed. Finally, the optimization results are exploited to infer the link between optimal reeling speed and tether force, which are both measured with high accuracy. Such a link is used to design a feedback controller that computes the reeling speed based on the measured tether force, in order to converge on the optimal force-speed manifold. Simulation results with a realistic model illustrate the effectiveness of the approach.
Berra et al. (Tue,) studied this question.