A Roadmap Towards Airborne Wind Energy in the Utility Sector

Kruijff, Michiel; Ruiterkamp, Richard

doi:10.1007/978-981-10-1947-0_26

Cited by 21 publications

(33 citation statements)

References 9 publications

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“…Tables 1 and 2 summarize the chosen constraints and bounds specified for trajectory optimization. The path constraints and variable bounds used in this work are compiled from the available literature Licitra et al, 2016;Zanon et al, 2013b;Kruijff and Ruiterkamp, 2018) and are adapted to large-scale AWE systems.…”

Section: Generation Of Reference Trajectoriesmentioning

confidence: 99%

“…Wind turbine wakes result from the interaction between wind turbines and the atmospheric boundary layer, and are characterized by a wind speed deficit and increased turbulence intensity (Stevens and Meneveau, 2017;Porte-Agel et al, 2020). For airborne wind energy systems, wake effects are generally considered small (Kruijff and Ruiterkamp, 2018) or are often ignored (Echeverri et al, 2020) due to the large swept area and relatively small wing dimensions. Hence, recent studies investigating performance losses (Malz et al, 2018) or layout optimization (Roque et al, 2020) in airborne wind energy farms did not consider wake effects.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, we consider large-scale multi-megawatt systems operating in both lift-and drag-modes and align our design with the proposed utility-scale system targets unveiled by the companies Ampyx Power (Kruijff and Ruiterkamp, 2018) and Makani Power (Harham, 2012).…”

Section: Introductionmentioning

confidence: 99%

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Large-eddy simulation of airborne wind energy farms

Haas

Schutter

Diehl

et al. 2021

Preprint

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Abstract. The future utility-scale deployment of airborne wind energy technologies requires the development of large-scale multi-megawatt systems. This study aims at quantifying the interaction between the atmospheric boundary layer (ABL) and large-scale airborne wind energy systems operating in a farm. To that end, we present a virtual flight simulator combining large-eddy simulations to simulate turbulent flow conditions and optimal control techniques for flight-path generation and tracking. The two-way coupling between flow and system dynamics is achieved by implementing an actuator sector method that we pair to a model predictive controller. In this study, we consider ground-based power generation pumping-mode AWE systems (lift-mode AWES) and on-board power generation AWE systems (drag-mode AWES). For the lift-mode AWES, we additionally investigate different reel-out strategies to reduce the interaction between the tethered wing and its own wake. Further, we investigate AWE parks consisting of 25 systems organized in 5 rows of 5 systems. For both lift- and drag-mode archetypes, we consider a moderate park layout with a power density of 10 MW km−2 achieved at a rated wind speed of 12 m s−1. For the drag-mode AWES, an additional park with denser layout and power density of 28 MW km−2 is also considered. The model predictive controller achieves very satisfactory flight-path tracking despite the AWE systems operating in fully waked, turbulent flow conditions. Furthermore, we observe significant wake effects for the utility-scale AWE systems considered in the study. Wake-induced performance losses increase gradually through the downstream rows of systems and reach in the last row of the parks up to 17 % for the lift-mode AWE park and up to 25 % and 45 % for the moderate and dense drag-mode AWE parks, respectively. For an operation period of 60 minutes at a below-rated reference wind speed of 10 m s−1, the lift-mode AWE park generates about 84.4 MW of power, corresponding to 82.5 % of the power yield expected when AWE systems operate ideally and interaction with the ABL is negligible. For the drag-mode AWE parks, the moderate and dense layouts generate about 86.0 MW and 72.9 MW of power, respectively, corresponding to 89.2 % and 75.6 % of the ideal power yield.

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Section: Generation Of Reference Trajectoriesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Large-eddy simulation of airborne wind energy farms

Haas

Schutter

Diehl

et al. 2021

Preprint

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“…We also provide an approximation of how the breakeven CapEx is distributed among different cost categories based on LCOE models for rigid wings (Echeverri et al 2020;Kruijff and Ruiterkamp 2018) and flexible wings (Heilmann 2012) in Table 5. As previously mentioned, some care must be taken when assessing these cost categories, as bottom-up LCOE projections for AWE systems are shrouded with uncertainty around the maturation of the supply chain for individual components.…”

Section: Cost Category Breakdownsmentioning

confidence: 99%

“…The value proposition for deploying AWE systems offshore is primarily related to reduced foundation size, which makes up a significant portion of the CapEx of fixed-bottom and floating traditional wind turbines (Stehly, Beiter, and Duffy 2020). The low overturning moments of a tethered system directly connected to the foundation can drastically reduce the size, and therefore the cost, of the support structure (Kruijff and Ruiterkamp 2018). Additional benefits are often cited, such as the strong offshore wind resource and the reduced demand (relative to traditional wind systems) for expensive and scarce installation vessels to construct and service an offshore AWE plant.…”

Section: Viability For Offshore Windmentioning

confidence: 99%

Airborne Wind Energy

Weber

Marquis

Cooperman

et al. 2021

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This section briefly describes the way in which this report addresses the congressional request regarding focus and scope, the consideration of AWE in relation to traditional wind energy, and the approach taken to develop the report. Addressing the Congressional Request: Focus and ScopeThis report describes technical analyses of various aspects of AWE provided to the U.S. Department of Energy (DOE) Wind Energy Technologies Office to underpin DOE's response to the congressional request for a report on AWE in the Energy Act of 2020, which states:-Not later than 180 days after the date of the enactment of this Act, the Secretary shall submit to the Committee on Science, Space, and Technology of the House of Representatives and the Committee on Energy and Natural Resources of the Senate a report on the potential for, and technical viability of, airborne wind energy systems to provide a significant source of energy in the United States.

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Improving reliability and safety of airborne wind energy systems

Salma

Friedl²,

Schmehl

2019

Wind Energy

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Airborne wind energy systems use tethered flying devices to harvest wind energy beyond the height range accessible to tower-based wind turbines. Current commercial prototypes have reached power ratings of up to several hundred kilowatts, and companies are aiming at long-term operation in relevant environments. As consequence, system reliability, operational robustness, and safety have become crucially important aspects of system development. In this study, we analyze the reliability and safety of a 100-kW technology development platform with the objective of achieving continuous automatic operation. We first outline the different components of the kite power system and its operational modes. In the next step, we identify failure modes, their causes, and effects by means of failure mode and effects analysis (FMEA) and fault tree analysis (FTA). Potentially hazardous situations and mechanisms which can render the system nonoperational are identified, and mitigation measures are proposed. We find that the majority of these measures can be performed by a failure detection, isolation, and recovery (FDIR) system for which we present a hierarchical architecture adapted from space industry. KEYWORDS airborne wind energy, fault detection, fault isolation, fault recovery, FDIR, FMEA, FTA, health monitoring, kite power, reliability, safety INTRODUCTIONThe increasing need for renewable energy has led to a widespread deployment of wind turbines: initially, only on-shore, but for more than a decade, also off-shore. 1 The trend goes to ever larger turbines with increasing capacity factors because the wind power density generally increases with the distance from the ground, as a result of the wind shear. 2 On the other hand, the cost of larger structures scales unfavorably with a square-cube law and modern wind turbines are approaching an economically feasible size limit. 3 Airborne wind energy (AWE) systems, on the other hand, use tethered flying devices to harvest wind energy beyond the height range accessible to tower-based turbines. 4,5 The use of a tether allows the harvesting height to be adjusted continuously to optimize the availability of the wind resource. Compared with harvesting at the fixed hub height of wind turbines, the wind power that is available 95% of the time increases roughly by a factor of two. 6 Of particular interest are deep-sea applications because a tower is in principle not needed for the operation of the system. The tether attaches to the ground station at sea level, which substantially reduces the structural loads and thus also the required material. 7,8 The lower material effort, the increased capacity factor, and the access to a so far unused wind resource render AWE a potential cornerstone in a future low-carbon energy economy.However, the technology is operationally more complex than conventional wind turbines. Most implemented concepts rely on aerodynamic lift, and the tethered flying devices can thus not be stopped immediately when unexpected wind conditions or system failures occur. Exact...

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A Roadmap Towards Airborne Wind Energy in the Utility Sector

Cited by 21 publications

References 9 publications

Large-eddy simulation of airborne wind energy farms

Large-eddy simulation of airborne wind energy farms

Airborne Wind Energy

Improving reliability and safety of airborne wind energy systems

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