Control-based optimization for tethered tidal kite
This submission includes three peer-reviewed (under review) papers from the researchers at North Carolina State University presenting control-based techniques to maximize effectiveness of a tethered tidal kite. Below are the abstracts of each file included in the submission.
Cobb TCST - Iterative learning for kite path optimization.pdf
This paper presents an iterative learning control-based approach for optimizing the flight path geometry of a tethered MHK system. Tethered MHK systems, which replace the tower and turbine of a conventional system with a tether and a lifting body, capture energy by driving a generator with the tension in the tether. By spooling out tether during the high tension portions of cross-current flight and spooling in during low tension portions, net positive energy is generated over one cycle. Because the net energy generation is sensitive to the shape of the flown path, we employ an iterative learning update law to adapt the path shape from one lap to the next. Additionally, we present a realistic system model, along with lower-level path-following and power take-off (PTO) controllers. We then demonstrate the efficacy of our algorithm on this model in both uniform and realistic flow environments.
Siddiqui ACC - Optimal spooling control of kites in variable flow.pdf
This work focuses on the development of an adaptive control strategy that fuses Gaussian process modeling and receding horizon control to ideally manage the tradeoff between exploration (i.e., maintaining an adequate map of the resource) and exploitation (i.e., carrying out a mission, which consists in this work of harvesting the resource). The use of a receding horizon formulation aids in the consideration of limited mobility, which is characteristic of dynamical systems. In this work, we focus on an airborne wind energy (AWE) system as a case study, where the system can vary its elevation angle (tether angle relative to the ground, which trades off higher efficiency with higher-altitude operation) and flight path parameters in order to maximize power output in a wind environment that is changing in space and time. We demonstrate the effectiveness of the proposed approach through a data-driven study on a rigid wing-based AWE system.
Reed ACC - Spatial optimization of kite paths.pdf
This paper presents a technique for maximizing the power production of a tethered marine energy-harvesting kite performing cross-current figure-eight flight in a 3D spatiotemporally varying flow environment. To generate a net positive power output, the kite employs a cyclic spooling method, where the kite is spooled out while flying in high-tension crosscurrent figure-eight flight, then spooled in radially towards the base-station under low tension.
Citation Formats
TY - DATA
AB - This submission includes three peer-reviewed (under review) papers from the researchers at North Carolina State University presenting control-based techniques to maximize effectiveness of a tethered tidal kite. Below are the abstracts of each file included in the submission.
Cobb TCST - Iterative learning for kite path optimization.pdf
This paper presents an iterative learning control-based approach for optimizing the flight path geometry of a tethered MHK system. Tethered MHK systems, which replace the tower and turbine of a conventional system with a tether and a lifting body, capture energy by driving a generator with the tension in the tether. By spooling out tether during the high tension portions of cross-current flight and spooling in during low tension portions, net positive energy is generated over one cycle. Because the net energy generation is sensitive to the shape of the flown path, we employ an iterative learning update law to adapt the path shape from one lap to the next. Additionally, we present a realistic system model, along with lower-level path-following and power take-off (PTO) controllers. We then demonstrate the efficacy of our algorithm on this model in both uniform and realistic flow environments.
Siddiqui ACC - Optimal spooling control of kites in variable flow.pdf
This work focuses on the development of an adaptive control strategy that fuses Gaussian process modeling and receding horizon control to ideally manage the tradeoff between exploration (i.e., maintaining an adequate map of the resource) and exploitation (i.e., carrying out a mission, which consists in this work of harvesting the resource). The use of a receding horizon formulation aids in the consideration of limited mobility, which is characteristic of dynamical systems. In this work, we focus on an airborne wind energy (AWE) system as a case study, where the system can vary its elevation angle (tether angle relative to the ground, which trades off higher efficiency with higher-altitude operation) and flight path parameters in order to maximize power output in a wind environment that is changing in space and time. We demonstrate the effectiveness of the proposed approach through a data-driven study on a rigid wing-based AWE system.
Reed ACC - Spatial optimization of kite paths.pdf
This paper presents a technique for maximizing the power production of a tethered marine energy-harvesting kite performing cross-current figure-eight flight in a 3D spatiotemporally varying flow environment. To generate a net positive power output, the kite employs a cyclic spooling method, where the kite is spooled out while flying in high-tension crosscurrent figure-eight flight, then spooled in radially towards the base-station under low tension.
AU - Vermillion, Chris
A2 - Cobb, Mitchell
A3 - Reed, James
A4 - Daniels, Joshua
A5 - Siddiqui, Ayaz
A6 - Wu, Max
A7 - Fathy, Hosam
A8 - Barton, Kira
A9 - Muglia, Michael
A10 - Haydon, Ben
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO -
KW - MHK
KW - Marine
KW - Hydrokinetic
KW - energy
KW - power
KW - kite
KW - control
KW - tidal kite
KW - spatial optimization
KW - CEC
KW - cyclic spooling
KW - airborne wind energy
KW - AWE
KW - Gaussian
KW - exploration
KW - exploitation
KW - tethered
KW - power take-off
KW - PTO
KW - model
KW - modeling
KW - cross-current
KW - controller
KW - tension
KW - figure-eight
KW - plant
KW - optimization
KW - spatial
KW - adaptive control
KW - receding horizon
KW - MATLAB
KW - cyclic control
KW - iterative learning
KW - path
KW - fly-gen
KW - ground-gen
KW - generator
LA - English
DA - 2020/03/02
PY - 2020
PB - North Carolina State University
T1 - Control-based optimization for tethered tidal kite
UR - https://data.openei.org/submissions/7986
ER -
Vermillion, Chris, et al. Control-based optimization for tethered tidal kite. North Carolina State University, 2 March, 2020, MHKDR. https://mhkdr.openei.org/submissions/343.
Vermillion, C., Cobb, M., Reed, J., Daniels, J., Siddiqui, A., Wu, M., Fathy, H., Barton, K., Muglia, M., & Haydon, B. (2020). Control-based optimization for tethered tidal kite. [Data set]. MHKDR. North Carolina State University. https://mhkdr.openei.org/submissions/343
Vermillion, Chris, Mitchell Cobb, James Reed, Joshua Daniels, Ayaz Siddiqui, Max Wu, Hosam Fathy, Kira Barton, Michael Muglia, and Ben Haydon. Control-based optimization for tethered tidal kite. North Carolina State University, March, 2, 2020. Distributed by MHKDR. https://mhkdr.openei.org/submissions/343
@misc{OEDI_Dataset_7986,
title = {Control-based optimization for tethered tidal kite},
author = {Vermillion, Chris and Cobb, Mitchell and Reed, James and Daniels, Joshua and Siddiqui, Ayaz and Wu, Max and Fathy, Hosam and Barton, Kira and Muglia, Michael and Haydon, Ben},
abstractNote = {This submission includes three peer-reviewed (under review) papers from the researchers at North Carolina State University presenting control-based techniques to maximize effectiveness of a tethered tidal kite. Below are the abstracts of each file included in the submission.
Cobb TCST - Iterative learning for kite path optimization.pdf
This paper presents an iterative learning control-based approach for optimizing the flight path geometry of a tethered MHK system. Tethered MHK systems, which replace the tower and turbine of a conventional system with a tether and a lifting body, capture energy by driving a generator with the tension in the tether. By spooling out tether during the high tension portions of cross-current flight and spooling in during low tension portions, net positive energy is generated over one cycle. Because the net energy generation is sensitive to the shape of the flown path, we employ an iterative learning update law to adapt the path shape from one lap to the next. Additionally, we present a realistic system model, along with lower-level path-following and power take-off (PTO) controllers. We then demonstrate the efficacy of our algorithm on this model in both uniform and realistic flow environments.
Siddiqui ACC - Optimal spooling control of kites in variable flow.pdf
This work focuses on the development of an adaptive control strategy that fuses Gaussian process modeling and receding horizon control to ideally manage the tradeoff between exploration (i.e., maintaining an adequate map of the resource) and exploitation (i.e., carrying out a mission, which consists in this work of harvesting the resource). The use of a receding horizon formulation aids in the consideration of limited mobility, which is characteristic of dynamical systems. In this work, we focus on an airborne wind energy (AWE) system as a case study, where the system can vary its elevation angle (tether angle relative to the ground, which trades off higher efficiency with higher-altitude operation) and flight path parameters in order to maximize power output in a wind environment that is changing in space and time. We demonstrate the effectiveness of the proposed approach through a data-driven study on a rigid wing-based AWE system.
Reed ACC - Spatial optimization of kite paths.pdf
This paper presents a technique for maximizing the power production of a tethered marine energy-harvesting kite performing cross-current figure-eight flight in a 3D spatiotemporally varying flow environment. To generate a net positive power output, the kite employs a cyclic spooling method, where the kite is spooled out while flying in high-tension crosscurrent figure-eight flight, then spooled in radially towards the base-station under low tension.},
url = {https://mhkdr.openei.org/submissions/343},
year = {2020},
howpublished = {MHKDR, North Carolina State University, https://mhkdr.openei.org/submissions/343},
note = {Accessed: 2025-05-03}
}
Details
Data from Mar 2, 2020
Last updated Mar 1, 2021
Submitted Dec 4, 2020
Organization
North Carolina State University
Contact
Chris Vermillion
919.515.5244
Authors
Original Source
https://mhkdr.openei.org/submissions/343Research Areas
Keywords
MHK, Marine, Hydrokinetic, energy, power, kite, control, tidal kite, spatial optimization, CEC, cyclic spooling, airborne wind energy, AWE, Gaussian, exploration, exploitation, tethered, power take-off, PTO, model, modeling, cross-current, controller, tension, figure-eight, plant, optimization, spatial, adaptive control, receding horizon, MATLAB, cyclic control, iterative learning, path, fly-gen, ground-gen, generatorDOE Project Details
Project Name Device Design and Robust Periodic Motion Control of an Ocean Kite System for Marine Hydrokinetic Energy Harvesting
Project Lead Carrie Noonan
Project Number EE0008635