Genetrix/TU Delft V3 Leading Edge Inflatable kite and TU Delft Kite Control Unit (8 November 2014). 102
Pietro Faggiani Researcher Delft University of Technology Faculty of Aerospace Engineering
Kluyverweg 1 2629 HS Delft The Netherlands faggianipietro@yahoo.it
www.kitepower.eu
Pumping Kites Wind Farm
Pietro Faggiani, Roland Schmehl, Rolf van der Vlugt Faculty of Aerospace Engineering, Delft University of Technology Harvesting wind energy with kites and converting it into
electricity is technically feasible, as demonstrated by sev-eral existing prototype installations. One of the dom-inant concepts, at least in terms of numbers of proto-type systems, is the conversion of the traction power of kites within pumping cycles, which is also the topic of the present study. For demonstration of economic viability the prototype systems need to achieve prolonged opera-tional times and may need to be scaled-up to the size and numbers applicable in the target market.
At this stage of development of the technology, the fol-lowing questions need to be answered
• Spacing requirements of individual units in a wind farm?
• Achievable power output per square metre ground sur-face area?
• Continuous average power output possible by operat-ing multiple units?
• Achievable levelised cost of energy (LCOE)?
The current study addresses these questions. The work is divided in two phases: first, the analysis of the individ-ual pumping kite system, then, the study of the entire kite wind farm.
The analysis of a single pumping kite system starts from an arbitrary choice of kite size. An analytical quasi-steady model is used to describe the traction power of the wing along the pumping cycle. This model has been validated by experimental results and comparison with a more accurate dynamic system model. The strong influence of operational parameters on the energy production
re-quires an optimisation process. A genetic algorithm is used to optimise the traction and the retraction force, the elevation angle and the maximum and minimum tether lengths for different wind speeds. By choosing sets of op-erational parameters within given ranges, the algorithm is able to optimise the power production, resembling the natural Darwinian selection process.
The optimised system is used to simulate a farm of sev-eral identical units. Some thoughts have been put in the spatial distribution and the operation of such farm and in-teresting results are derived. The LCOE is finally used as an optimisation criterion for the kite size.
The optimal unit for the given prescribed wind con-ditions, appears to be powered by a 250 m2
soft-kite,achieving a net power output over the cycle of 90 kW. It is interesting to understand the effects on the cumu-lative power production of the number of kites and the wind speed. The more units are installed in the farm the more constant is the power produced. Considering the three-dimensional spatial distribution of the kites in the farm, units could be placed much closer than wind tur-bines leading to a very high installed power per land oc-cupied of 87 W/m2. The LCOE of the farm is computed to
be in the range of 95 to 105 e/MWh, depending on the number of kites in the farm and the assumptions made on costs of various system components.
The outcome of this study shows a very promising tech-nical and economical potential of the technology. It will hopefully serve as reference to justify the great expecta-tions of the various research groups in the field.
