Airborne Wind Energy System Analysis and Design Optimization
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University of Cincinnati / OhioLINK
2020
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| Online Access: | http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168644639446 |
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ndltd-OhioLink-oai-etd.ohiolink.edu-ucin15921686446394462021-08-03T07:15:21Z Airborne Wind Energy System Analysis and Design Optimization Aull, Mark J. Aerospace Materials AWE airborne wind energy performance analysis design optimization stochastical robustness Airborne wind energy (AWE) used tethered aircraft to harvest wind energy, with significant potential advantages over conventional wind turbines. Aerodynamic and tether forces propel the aircraft perpendicular to the wind, analogous to a wind turbine blade, but with significantly less structural weight for the same power production. The logistical benefits of AWE promise a lower cost of energy, higher performance for mobile wind systems, and easier installation for offshore systems.Because AWE systems are a relatively new concept (many are in various states of R\&D, but no commercial AWE wind farms currently exist), and because they are significantly more complex to design, analyze, and test than traditional wind turbines, better analysis tools are important for the technology to mature. One desirable capability is a performance analysis tool that calculates power output quickly enough to be feasible for system design optimization and versatile enough to permit changing most input parameters without requiring a higher level analyses (like a control design, CFD simulation, etc.) High fidelity simulations are computationally intensive enough to be undesirable for iterating through parameters for design optimization.The analysis tool developed is unique and distinct from a simulator in several ways. It uses Fourier series inputs to define the path and velocity of the aircraft, guaranteeing a closed, steady state cycle (rather than requiring iterations to converge to a steady state solution), then calculates attitudes, forces, and moments required to follow that trajectory. No controller is required and therefore there is no need to design or tune a controller for each set of system parameters, and there are no deviations from the proscribed trajectory or instabilities due to the controller. Conversely, the analysis tool produces estimated control signals required to pilot a simulator operating in the same conditions. With this analysis tool, analyzing a single case (determined by path, velocity profile, wind profile, and other parameters) is very fast, though ensuring that a set of constraints is met requires iteration. Comparing different system designs at the same condition is relatively computationally inexpensive, therefore iterating over system designs to minimize a cost function is feasible. For maximizing energy output, it is possible to use an approximation for the velocity that maximizes energy harvested at each point as a good initial condition for iteration.Results from the analysis tool (which uses approximations such as a rigid tether and constant lift and drag coefficients) match well with results from higher fidelity simulations that don't use those approximations and is capable of generating feed-forward control signals to drive the higher fidelity simulation. The tool has also been used to optimize system parameters, leading to the conclusion that the proper size for an AWE system is the largest size where mass is scaling with wing area or the smallest size where mass is scaling faster than wing area. The analysis tool has been used to analyze the statistical robustness of a set of trajectories and found that robustness to wind gusts has a significant impact on performance, therefore accurate wind speed and direction estimates are critical. 2020-06-15 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168644639446 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168644639446 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws. |
| collection |
NDLTD |
| language |
English |
| sources |
NDLTD |
| topic |
Aerospace Materials AWE airborne wind energy performance analysis design optimization stochastical robustness |
| spellingShingle |
Aerospace Materials AWE airborne wind energy performance analysis design optimization stochastical robustness Aull, Mark J. Airborne Wind Energy System Analysis and Design Optimization |
| author |
Aull, Mark J. |
| author_facet |
Aull, Mark J. |
| author_sort |
Aull, Mark J. |
| title |
Airborne Wind Energy System Analysis and Design Optimization |
| title_short |
Airborne Wind Energy System Analysis and Design Optimization |
| title_full |
Airborne Wind Energy System Analysis and Design Optimization |
| title_fullStr |
Airborne Wind Energy System Analysis and Design Optimization |
| title_full_unstemmed |
Airborne Wind Energy System Analysis and Design Optimization |
| title_sort |
airborne wind energy system analysis and design optimization |
| publisher |
University of Cincinnati / OhioLINK |
| publishDate |
2020 |
| url |
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1592168644639446 |
| work_keys_str_mv |
AT aullmarkj airbornewindenergysystemanalysisanddesignoptimization |
| _version_ |
1719457668446289920 |