This paper presents simulation and experimental results regarding a new class of wind energy generators, denoted as KiteGen, which employ power kites to capture high altitude wind power. A realistic kite model, which includes the kite aerodynamic characteristics and the effects of line weight and drag forces, is used to describe the system dynamics. Nonlinear model predictive control techniques, together with an efficient implementation based on set membership function approximation theory, are employed to maximize the energy obtained by KiteGen, while satisfying input and state constraints. Two different kinds of KiteGen are investigated through numerical simulations, the yo-yo configuration and the carousel configuration, respectively. For each configuration, a generator with the same kite and nominal wind characteristics is considered. A novel control strategy for the carousel configuration, with respect to previous works, is also introduced. The simulation results show that the power generation potentials of the yo-yo and carousel configurations are very similar. Thus, the choice between these two configurations for further development of a medium-to-large scale generator will be made on the basis of technical implementation problems and of other indexes like construction costs and generated power density with respect to land occupation. Experimental data, collected using the small-scale KiteGen prototype built at Politecnico di Torino, are compared to simulation results. The good matching between simulation and real measured data increases the confidence with the presented simulation results, which show that energy generation with controlled power kites can represent a quantum leap in wind power technology, promising to obtain renewable energy from a source largely available almost everywhere, with production costs lower than those of fossil sources. © 2009 IEEE.

High altitude wind energy generation using controlled power kites

CANALE, MASSIMO;Fagiano, Lorenzo;
2010-01-01

Abstract

This paper presents simulation and experimental results regarding a new class of wind energy generators, denoted as KiteGen, which employ power kites to capture high altitude wind power. A realistic kite model, which includes the kite aerodynamic characteristics and the effects of line weight and drag forces, is used to describe the system dynamics. Nonlinear model predictive control techniques, together with an efficient implementation based on set membership function approximation theory, are employed to maximize the energy obtained by KiteGen, while satisfying input and state constraints. Two different kinds of KiteGen are investigated through numerical simulations, the yo-yo configuration and the carousel configuration, respectively. For each configuration, a generator with the same kite and nominal wind characteristics is considered. A novel control strategy for the carousel configuration, with respect to previous works, is also introduced. The simulation results show that the power generation potentials of the yo-yo and carousel configurations are very similar. Thus, the choice between these two configurations for further development of a medium-to-large scale generator will be made on the basis of technical implementation problems and of other indexes like construction costs and generated power density with respect to land occupation. Experimental data, collected using the small-scale KiteGen prototype built at Politecnico di Torino, are compared to simulation results. The good matching between simulation and real measured data increases the confidence with the presented simulation results, which show that energy generation with controlled power kites can represent a quantum leap in wind power technology, promising to obtain renewable energy from a source largely available almost everywhere, with production costs lower than those of fossil sources. © 2009 IEEE.
2010
Constrained control; Nonlinear systems; Predictive control; Renewable energy; Wind energy; Control and Systems Engineering; Electrical and Electronic Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1049089
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