M. Schelbergen
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1
The flexible-membrane kite employed by some airborne wind energy systems uses a suspended control unit, which experiences a characteristic swinging motion relative to the top of the kite during sharp turning manoeuvres. This paper assesses the accuracy of a two-point kite model in resolving this swinging motion using two different approaches: approximating the motion as a transition through steady-rotation states and solving the motion dynamically. The kite is modelled with two rigidly linked point masses representing the control unit and wing, which conveniently extend a discretised tether model. The tether-kite motion is solved by prescribing the trajectory of the wing point mass to replicate a figure-eight manoeuvre from the flight data of an existing prototype. The computed pitch and roll of the kite are compared against the attitude measurements of two sensors mounted to the wing. The two approaches compute similar pitch and roll angles during the straight sections of the figure-eight manoeuvre and match measurements within 3°. However, during the turns, the dynamically solved pitch and roll angles show systematic differences compared to the steady-rotation solution. As a two-point kite model resolves the roll, the lift force may tilt along with the kite, which is identified as the driving mechanism for turning flexible kites. Moreover, the two-point kite model complements the aerodynamic model as it allows for computing the angle of attack of the wing by resolving the pitch. These characteristics improve the generalisation of the kite model compared to a single-point model with little additional computational effort.
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The flexible-membrane kite employed by some airborne wind energy systems uses a suspended control unit, which experiences a characteristic swinging motion relative to the top of the kite during sharp turning manoeuvres. This paper assesses the accuracy of a two-point kite model in resolving this swinging motion using two different approaches: approximating the motion as a transition through steady-rotation states and solving the motion dynamically. The kite is modelled with two rigidly linked point masses representing the control unit and wing, which conveniently extend a discretised tether model. The tether-kite motion is solved by prescribing the trajectory of the wing point mass to replicate a figure-eight manoeuvre from the flight data of an existing prototype. The computed pitch and roll of the kite are compared against the attitude measurements of two sensors mounted to the wing. The two approaches compute similar pitch and roll angles during the straight sections of the figure-eight manoeuvre and match measurements within 3°. However, during the turns, the dynamically solved pitch and roll angles show systematic differences compared to the steady-rotation solution. As a two-point kite model resolves the roll, the lift force may tilt along with the kite, which is identified as the driving mechanism for turning flexible kites. Moreover, the two-point kite model complements the aerodynamic model as it allows for computing the angle of attack of the wing by resolving the pitch. These characteristics improve the generalisation of the kite model compared to a single-point model with little additional computational effort.
Power to the airborne wind energy performance model
Estimating long-term energy production with an emphasis on pumping flexible-kite systems
The potential of utility-scale airborne wind energy (AWE) systems to contribute significantly to the energy transition hinges on their large-scale deployment, which depends on the cost-competitiveness and complementarity with conventional wind turbines. Central to the assessment of these metrics is understanding long-term energy production, which is influenced by the variability of wind profiles. This thesis investigates the significance of wind profile variability on annual energy production estimation for AWE systems. The study establishes the climatology of vertical wind profiles and expands flight operation models of AWE systems. By synthesising these aspects, a new energy production estimation framework is developed to incorporate variations in the wind profile shape. This framework is utilised to assess the impact of different wind profile shapes on the energy production estimation. The research underlines the need to move away from conventional wind energy calculation methods and offers a more suitable alternative for AWE systems. The framework offers a valuable tool for increasing the understanding of the viability of large-scale deployment of AWE systems.
...
The potential of utility-scale airborne wind energy (AWE) systems to contribute significantly to the energy transition hinges on their large-scale deployment, which depends on the cost-competitiveness and complementarity with conventional wind turbines. Central to the assessment of these metrics is understanding long-term energy production, which is influenced by the variability of wind profiles. This thesis investigates the significance of wind profile variability on annual energy production estimation for AWE systems. The study establishes the climatology of vertical wind profiles and expands flight operation models of AWE systems. By synthesising these aspects, a new energy production estimation framework is developed to incorporate variations in the wind profile shape. This framework is utilised to assess the impact of different wind profile shapes on the energy production estimation. The research underlines the need to move away from conventional wind energy calculation methods and offers a more suitable alternative for AWE systems. The framework offers a valuable tool for increasing the understanding of the viability of large-scale deployment of AWE systems.
Airborne wind energy (AWE) systems harness energy at heights beyond the reach of tower-based wind turbines. To estimate the annual energy production (AEP), measured or modelled wind speed statistics close to the ground are commonly extrapolated to higher altitudes, introducing substantial uncertainties. This study proposes a clustering procedure for obtaining wind statistics for an extended height range from modelled datasets that include the variation in the wind speed and direction with height. K-means clustering is used to identify a set of wind profile shapes that characterise the wind resource. The methodology is demonstrated using the Dutch Offshore Wind Atlas for the locations of the met masts IJmuiden and Cabauw, 85 km off the Dutch coast in the North Sea and in the centre of the Netherlands, respectively. The cluster-mean wind profile shapes and the corresponding temporal cycles, wind properties, and atmospheric stability are in good agreement with the literature. Finally, it is demonstrated how a set of wind profile shapes is used to estimate the AEP of a small-scale pumping AWE system located at Cabauw, which requires the derivation of a separate power curve for each wind profile shape. Studying the relationship between the estimated AEP and the number of site-specific clusters used for the calculation shows that the difference in AEP relative to the converged value is less than 3 % for four or more clusters.
...
Airborne wind energy (AWE) systems harness energy at heights beyond the reach of tower-based wind turbines. To estimate the annual energy production (AEP), measured or modelled wind speed statistics close to the ground are commonly extrapolated to higher altitudes, introducing substantial uncertainties. This study proposes a clustering procedure for obtaining wind statistics for an extended height range from modelled datasets that include the variation in the wind speed and direction with height. K-means clustering is used to identify a set of wind profile shapes that characterise the wind resource. The methodology is demonstrated using the Dutch Offshore Wind Atlas for the locations of the met masts IJmuiden and Cabauw, 85 km off the Dutch coast in the North Sea and in the centre of the Netherlands, respectively. The cluster-mean wind profile shapes and the corresponding temporal cycles, wind properties, and atmospheric stability are in good agreement with the literature. Finally, it is demonstrated how a set of wind profile shapes is used to estimate the AEP of a small-scale pumping AWE system located at Cabauw, which requires the derivation of a separate power curve for each wind profile shape. Studying the relationship between the estimated AEP and the number of site-specific clusters used for the calculation shows that the difference in AEP relative to the converged value is less than 3 % for four or more clusters.
The quasi-steady performance model (QSM) has been developed specifically for pumping airborne wind energy systems using flexible membrane wings. In this study, we validate this model using a comprehensive set of flight data that includes 87 consecutive pumping cycles and is acquired with the development platform of Kitepower B.V. The aerodynamic properties of the kite are determined using onboard measurements of the relative flow velocity. We found that neglecting the vertical wind component and straightening and slacking motion of the tether lead to substantial errors in the kite velocity calculated using the system model. A reasonable agreement between the QSM simulations and flight data can be obtained by multiplying the kite's drag coefficient by a fudge factor and thereby turning the QSM into a grey-box model. The model accuracy is statistically evaluated as opposed to only evaluating a single pumping cycle per system configuration as done in earlier research.
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The quasi-steady performance model (QSM) has been developed specifically for pumping airborne wind energy systems using flexible membrane wings. In this study, we validate this model using a comprehensive set of flight data that includes 87 consecutive pumping cycles and is acquired with the development platform of Kitepower B.V. The aerodynamic properties of the kite are determined using onboard measurements of the relative flow velocity. We found that neglecting the vertical wind component and straightening and slacking motion of the tether lead to substantial errors in the kite velocity calculated using the system model. A reasonable agreement between the QSM simulations and flight data can be obtained by multiplying the kite's drag coefficient by a fudge factor and thereby turning the QSM into a grey-box model. The model accuracy is statistically evaluated as opposed to only evaluating a single pumping cycle per system configuration as done in earlier research.
Journal article
(2019)
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Philip Bechtle, Mark Schelbergen, Roland Schmehl, Udo Zillmann, Simon Watson
We compare the available wind resources for conventional wind turbines and for airborne wind energy systems. Accessing higher altitudes and continuously adjusting the harvesting operation to the wind resource substantially increases the potential energy yield. The study is based on the ERA5 reanalysis data which covers a period of 7 years with hourly estimates at a surface resolution of 31 × 31 km and a vertical resolution of 137 barometric altitude levels. We present detailed wind statistics for a location in the English Channel and then expand the analysis to a surface grid of Western and Central Europe with a resolution of 110 × 110 km. Over the land mass and coastal areas of Europe we find that compared to a fixed harvesting height at the approximate hub height of wind turbines, the wind power density which is available for 95% of the time increases by a factor of two.
...
We compare the available wind resources for conventional wind turbines and for airborne wind energy systems. Accessing higher altitudes and continuously adjusting the harvesting operation to the wind resource substantially increases the potential energy yield. The study is based on the ERA5 reanalysis data which covers a period of 7 years with hourly estimates at a surface resolution of 31 × 31 km and a vertical resolution of 137 barometric altitude levels. We present detailed wind statistics for a location in the English Channel and then expand the analysis to a surface grid of Western and Central Europe with a resolution of 110 × 110 km. Over the land mass and coastal areas of Europe we find that compared to a fixed harvesting height at the approximate hub height of wind turbines, the wind power density which is available for 95% of the time increases by a factor of two.
Abstract
(2019)
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Philip Bechtle, Mark Schelbergen, Roland Schmehl, Udo Zillmann, Maximilian Rueger, Elena Malz, Fiona Paulus, Michelle Birr
Airborne Wind Energy Systems (AWES) have different power generation characteristics than conventional wind turbines, which can not be accurately captured in the traditional power curve. One important aspect is that it can harvest wind energy in a much wider range of altitudes than conventional wind turbines. Theoretically also High Altitude Winds (HAW) can be harnessed and the systems can be placed at a larger variety of sites.
...
Airborne Wind Energy Systems (AWES) have different power generation characteristics than conventional wind turbines, which can not be accurately captured in the traditional power curve. One important aspect is that it can harvest wind energy in a much wider range of altitudes than conventional wind turbines. Theoretically also High Altitude Winds (HAW) can be harnessed and the systems can be placed at a larger variety of sites.
Airborne Wind Energy (AWE) systems use tethered flying devices to access higher altitudes, typically up to 500 meter, where wind is generally stronger and more persistent. To estimate the Annual Energy Production (AEP) of AWE systems, the wind speed statistics close to the ground are typically extrapolated to higher altitudes, introducing substantial uncertainties. A methodology is developed for characterising a site’s wind resource using a set of wind profile shapes. It is demonstrated how this wind resource representation is used together with a performance model to do fast AEP calculations for flexible-kite pumping AWE systems.
...
Airborne Wind Energy (AWE) systems use tethered flying devices to access higher altitudes, typically up to 500 meter, where wind is generally stronger and more persistent. To estimate the Annual Energy Production (AEP) of AWE systems, the wind speed statistics close to the ground are typically extrapolated to higher altitudes, introducing substantial uncertainties. A methodology is developed for characterising a site’s wind resource using a set of wind profile shapes. It is demonstrated how this wind resource representation is used together with a performance model to do fast AEP calculations for flexible-kite pumping AWE systems.