Abstract
The traction force of a kite can be used to drive a cyclic motion for extracting wind energy from the atmosphere. This paper presents a novel quasi-steady modelling framework for predicting the power generated over a full pumping cycle. The cycle is divided into traction, retraction and transition phases, each described by an individual set of analytic equations. The effect of gravity on the airborne system components is included in the framework. A trade-off is made between modelling accuracy and computation speed such that the model is specifically useful for system optimisation and scaling in economic feasibility studies. Simulation results are compared to experimental measurements of a 20 kW kite power system operated up to a tether length of 720 m. Simulation and experiment agree reasonably well, both for moderate and for strong wind conditions, indicating that the effect of gravity has to be taken into account for a predictive performance simulation.
Highlights
The pumping kite concept provides a simple yet effective solution for wind energy conversion at a potentially low cost [1]
The presented modelling framework is suitable to derive a fast estimate of the system performance
The present study comprises a quasi-steady modelling framework for a pumping kite power system and a comprehensive validation of this framework based on experimental data
Summary
The pumping kite concept provides a simple yet effective solution for wind energy conversion at a potentially low cost [1]. Various modelling frameworks have been proposed to predict the traction force and power generated by a tethered wing, both for the production of electricity [2e7] and for the propulsion of ships [8e13]. [8,9] has been validated experimentally, yet not assessed for its potential to predict the power generated over a full cycle of a pumping system. Dynamic models have been proposed by Refs. [14e19] to address challenges in the field of control or by Ref. Recent studies have used measurement data from full-scale demonstrator systems to analyse the turning dynamics of kites and to assess flight control algorithms [21,22]
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