Research Papers

Lab-Scale Experimental Characterization and Dynamic Scaling Assessment for Closed-Loop Crosswind Flight of Airborne Wind Energy Systems

[+] Author and Article Information
Mitchell Cobb

Department of Mechanical Engineering,
University of North Carolina at Charlotte,
Charlotte, NC 28223
e-mail: mcobb12@uncc.edu

Nihar Deodhar

Department of Mechanical Engineering,
University of North Carolina at Charlotte,
Charlotte, NC 28223
e-mail: ndeodhar@uncc.edu

Christopher Vermillion

Department of Mechanical Engineering,
University of North Carolina at Charlotte,
Charlotte, NC 28223
e-mail: cvermill@uncc.edu

1Corresponding author.

2Present address: Altaeros Energies, Somerville, MA 02143.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received May 6, 2017; final manuscript received November 15, 2017; published online January 16, 2018. Assoc. Editor: Mazen Farhood.

J. Dyn. Sys., Meas., Control 140(7), 071005 (Jan 16, 2018) (12 pages) Paper No: DS-17-1241; doi: 10.1115/1.4038650 History: Received May 06, 2017; Revised November 15, 2017

This paper presents the experimental validation and dynamic similarity analysis for a lab-scale version of an airborne wind energy (AWE) system executing closed-loop motion control. Execution of crosswind flight patterns, achieved in this work through the asymmetric motion of three tethers, enables dramatic increases in energy generation compared with stationary operation. Achievement of crosswind flight in the lab-scale experimental framework described herein allows for rapid, inexpensive, and dynamically scalable characterization of new control algorithms without recourse to expensive full-scale prototyping. We first present the experimental setup, then derive dynamic scaling relationships necessary for the lab-scale behavior to match the full-scale behavior. We then validate dynamic equivalence of crosswind flight over a range of different scale models of the Altaeros Buoyant airborne turbine (BAT). This work is the first example of successful lab-scale control and measurement of crosswind motion for an AWE system across a range of flow speeds and system scales. The results demonstrate that crosswind flight can achieve significantly more power production than stationary operation, while also validating dynamic scaling laws under closed-loop control.

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Grahic Jump Location
Fig. 1

AWE systems that have been implemented at full scale, including the (a) KITEnrg system [4], (b) Altaeros BAT [5], and (c) Google-owned Makani Power prototype [1]

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Fig. 2

Image of prototype full-scale system, the Altaeros BAT, showing annular shroud, turbine, tethers, and ground station (Adapted from Ref. [5])

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Fig. 7

Comparison of the control structure of lab-scale and full-scale system. The new, enhanced motion capture and image processing algorithms detailed in this paper are located in the feedback loop of the lab-scale system. While the plant and feedback instrumentation differ between setups, the controller does not. The variable, pi, is a matrix containing four scalars, the x and y pixel coordinates of each set of dots within the image imgj. This is explained in detail in Sec. 3.1.

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Fig. 6

Image of experimental equipment showing the water channel, host computer, target computer, DC motors (inset left), scale model, and video cameras. The DC motors and tether spools are located above the water channel, outside the frame of the main image.

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Fig. 5

Top-down (left) and frontal view of AWE system (right) depicting the method of inducing crosswind flight. The top-down view shows free stream velocity of fluid flow, vf, velocity vector of model, v, and velocity vector of apparent wind as experienced by the model va. The frontal view shows how the aerodynamic lift vector generates significant lateral force when the model is rolled.

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Fig. 4

Block diagram of the flight control strategy showing setpoints zsp, θsp, and ϕsp, tether release speed commands, u1, u2, and u3 as well as the measured altitude, pitch, and roll zg,m, θm, and ϕm

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Fig. 3

Comparison of full-scale system (left) with dynamic model approximation (right) which treats the three-tether system as a single tether with a spherical bridle joint

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Fig. 8

Schematic depiction of three-tether AWE system based on the Altaeros BAT with zero roll, pitch, and yaw, including camera locations, tether lengths (li), and azimuth angle (Φ)

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Fig. 9

Image of 3D printed, 1:100 scale model of the Altaeros BAT (approximately 8 cm in length), showing image tracking dot sets as well as two of the three tether attachment points. The starboard tether attachment point is not visible in the image.

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Fig. 10

Three different scale models of the Altaeros BAT. The smallest (left) has a characteristic length that is 75% of the characteristic length of the 1:100 model (middle). The largest (right) has a characteristic length that is 125% of the characteristic length of the 1:100 model (middle).

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Fig. 11

Comparison of controlled roll angle plotted against time, t (top), and normalized time, t¯ (bottom)

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Fig. 12

Comparison of uncontrolled yaw angle plotted against time, t (top), and normalized time, t¯ (bottom)

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Fig. 13

Comparison of uncontrolled azimuth angle plotted against time, t (top) and normalized time, t¯ (bottom)

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Fig. 14

The top plots shows the measured mean power ratios, PA,Bs, PA,Bm, or PA,Bl plotted against the corresponding set of roll setpoint periods TA,Bs, TA,Bm, or TA,Bl along with their associated best fit curves given by Eqs. (31) and (32). The bottom plot shows the same for the power ratio 85th percentile.

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Fig. 15

The top plot shows the power ratio plotted against the normalized roll setpoint period calculated from nominal time scale factors, αs, αm, and αl. The bottom plot shows the mean power ratio plotted against the normalized roll setpoint period calculated by using the scale factors α̂s and α̂l given by Eq. (33).



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