| 1. |
- De Schutter, Jochem, et al.
(författare)
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AWEbox: An Optimal Control Framework for Single- and Multi-Aircraft Airborne Wind Energy Systems
- 2023
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Ingår i: Energies. - : MDPI AG. - 1996-1073 .- 1996-1073. ; 16:4
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present AWEbox, a Python toolbox for modeling and optimal control of multi-aircraft systems for airborne wind energy (AWE). AWEbox provides an implementation of optimization-friendly multi-aircraft AWE dynamics for a wide range of system architectures and modeling options. It automatically formulates typical AWE optimal control problems based on these models, and finds a numerical solution in a reliable and efficient fashion. To obtain a high level of reliability and efficiency, the toolbox implements different homotopy methods for initial guess refinement. The first type of method produces a feasible initial guess from an analytic initial guess based on user-provided parameters. The second type implements a warm-start procedure for parametric sweeps. We investigate the software performance in two different case studies. In the first case study, we solve a single-aircraft reference problem for a large number of different initial guesses. The homotopy methods reduce the expected computation time by a factor of 1.7 and the peak computation time by a factor of eight, compared to when no homotopy is applied. Overall, the CPU timings are competitive with the timings reported in the literature. When the user initialization draws on expert a priori knowledge, homotopies do not increase expected performance, but the peak CPU time is still reduced by a factor of 5.5. In the second case study, a power curve for a dual-aircraft lift-mode AWE system is computed using the two different homotopy types for initial guess refinement. On average, the second homotopy type, which is tailored for parametric sweeps, outperforms the first type in terms of CPU time by a factor of three. In conclusion, AWEbox provides an open-source implementation of efficient and reliable optimal control methods that both control experts and non-expert AWE developers can benefit from.
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| 2. |
- Ehnberg, Jimmy, 1976, et al.
(författare)
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Optimization of Off-Shore Wind Power Plants Collection Grids
- 2013
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Ingår i: 12th Wind Integration Workshop.
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Konferensbidrag (refereegranskat)abstract
- This paper is based on the optimization of the total life time cost for the collection grids for an off-shore wind power plants. It is obvious that more power production, and thereby more revenues, can be expected with a high degree of redundancy. Even though full redundancy is theoretically possible, the upper economical viable limit has shown to be lower. Adding more reliability increases the investment costs, whereas the benefits are not increasing correspondingly. The optimization is demonstrated for a wind power plant layout with 8 wind turbines of 6 MW. Different scenarios are considered, from a radial layout up to a full redundancy solution. The different scenarios are based on standardized cable types and compared in relation to total life time cost. The total life time cost is based on capital costs, operational costs and production losses due to cable failures. The impacts of different average wind speeds, electricity prices, failure rates and mean repair times are investigated, presented and discussed. Finally a comparison between the layouts is done, which results in a minimum of costs at a redundancy around 70-75% for a wind power plant with typical conditions for the North Sea.
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| 3. |
- Leuthold, Rachel, et al.
(författare)
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Operational Regions of a Multi-Kite AWE System
- 2018
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Ingår i: 2018 European Control Conference, ECC 2018. ; , s. 52-57
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Konferensbidrag (refereegranskat)abstract
- Multiple-kite airborne wind energy systems (MAWES) aim to efficiently harvest the stronger, less-intermittent winds at high altitude without material-intensive towers. Solving a series of optimal control problems for two-kite MAWES, we show that pumping-cycle MAWES have three distinct operational regions: Region I, where power is consumed to stay aloft; Region II, where the power harvesting factor grows until the design wind speed; and Region III, where the power extraction is curtailed so as to respect the physical limitations of the system. The actuator disk (AD) method is arguably the simplest tool to model aerodynamic induction effects, though its validity is limited. In this paper, we show that AD is not valid for Region I.
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| 4. |
- Malz, Elena, 1990, et al.
(författare)
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A Quantification of the Performance Loss of Power Averaging in Airborne Wind Energy Farms
- 2018
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Ingår i: 2018 European Control Conference, ECC 2018. - 9783952426982 ; , s. 58-63
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Konferensbidrag (refereegranskat)abstract
- Airborne wind energy (AWE) is a promising source of renewable energy, with a potential of offering great and reliable energy yields. However, in addition to the usual power intermittency of renewable source of energies, AWE systems have a large and periodic fluctuation of their power output, and even consume power at certain phases of their orbit in some modes of power generation. These fluctuations may become a significant obstacle to a large-scale deployment of AWE systems in the power grid. For a large AWE farm, these fluctuations can be mitigated by power averaging, at the expense of fixing the AWE systems orbit times. This requirement removes the possibility for individual AWE systems within a wind farm to optimize their orbit time for their specific, local wind conditions, entailing a loss of performance. In order to assess the viability of mitigating the power fluctuation by power averaging at the wind farm level, this paper quantifies the loss of performance it yields.
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| 5. |
- Malz, Elena, 1990, et al.
(författare)
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A reference model for airborne wind energy systems for optimization and control
- 2019
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Ingår i: Renewable Energy. - : Elsevier BV. - 0960-1481 .- 1879-0682. ; 140, s. 1004-1011
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Tidskriftsartikel (refereegranskat)abstract
- Airborne Wind Energy (AWE) is a promising new technology, and attracts a growing academic and industrial attention. Important research efforts have been deployed to develop prototypes in order to test the technology, generate control algorithms and optimize the efficiency of AWE systems. By today, a large set of control and optimization methods is available for AWE systems. However, because no validated reference model is available, there is a lack of benchmark for these methods. In this paper, we provide a reference model for pumping mode AWE systems based on rigid wings. The model describes the flight dynamics of a tethered 6 degrees of freedom (DOF) rigid body aircraft in form of differential-algebraic equations, based on Lagrange dynamics. With the help of least squares fitting the model is assessed using real flight data from the Ampyx Power prototype AP2. The model equations are smooth and have a low symbolic complexity, so as to make the model ideal for optimization and control. The information given in this paper aims at providing AWE researchers with a model that has been validated against flight data and that is well suited for trajectory and power output simulation and optimization.
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| 6. |
- Malz, Elena, 1990
(författare)
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Airborne Wind Energy - to fly or not to fly?
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis investigates crosswind Airborne Wind Energy Systems (AWESs) in terms of power production and potential role in future electricity generation systems. The perspective ranges from the small scale, modelling AWE as a single system, to the large, implementing AWESs in regional electricity systems. To estimate the AWES power production, the thesis provides a dynamic system model that serves as the basis for all the work. The model describes the flight dynamics of a rigid wing that is exposed to tether and aerodynamic forces controlled by flight control surfaces. Index-3 Differential Algebraic Equations (DAEs) based on Lagrangian mechanics describe the dynamics. This model is validated by fitting it to real flight measurements obtained with a pumping-mode AWES, the prototype AP2 by Ampyx Power. The optimal power production of an AWES depends on complex trade-offs; this motivates formulating the power production computation as an Optimal Control Problem (OCP). The thesis presents the numerical methods needed to discretize the OCP and solve the resulting Nonlinear Program (NLP). Large-scale implementation of AWESs raises challenges related to variability in power production on the time scale of minutes to weeks. For the former, we investigate the periodic fluctuations in the power output of a single AWES. These fluctuations can be severe when operating a wind farm and have to be considered and reduced for an acceptable grid integration. We analyse the option of controlling the flight trajectories of the individual systems in a farm so that the total power output of the farm is smoothed. This controlled operation fixes the system's trajectory, reducing the ability to maximize the power output of individual AWESs to local wind conditions. We quantify the lost power production if the systems are controlled such that the total farm power output is smoothed. Results show that the power difference between the optimal and fixed trajectory does not exceed 4% for the systems modelled in the study. The variations in AWESs power production on the timescale of hours to weeks are particularly relevant to the interaction between AWE and other power generation technologies. Investigating AWESs in an electricity system context requires power-generation profiles with high spatio-temporal resolution, which means solving a large number of OCPs. In order to efficiently solve these numerous OCPs in a sequential manner, this thesis presents a homotopy-path-following method combined with modifications to the NLP solver. The implementation shows a 20-fold reduction in computation time compared to the original method for solving the NLP for AWES power optimization. For large wind-data sets, a random forest regression model is trained to a high accuracy, providing an even faster computation. The annual generation profiles for the modelled systems are computed using ERA5 wind data for several locations and compared to the generation profile for a traditional wind turbine. The results show that the profiles are strongly correlated in time, which is a sobering fact in terms of technology competition. However, the correlation is weaker in locations with high wind shear. The potential role of AWESs in the future electricity system is further investigated. This thesis implements annual AWE-farm generation profiles into a cost-optimizing electricity system model. We find that AWE is most valuable to the electricity system if installed at sites with low wind speed within a region. At greater shares of the electricity system, even if AWESs could demonstrate lower costs compared to wind turbines, AWE would merely substitute for them instead of increasing the total share of wind energy in the system. This implies that the economic value of an AWES is limited by its cost relative to traditional wind turbines.
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| 7. |
- Malz, Elena, 1990, et al.
(författare)
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Computing the power profiles for an Airborne Wind Energy system based on large-scale wind data
- 2020
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Ingår i: Renewable Energy. - : Elsevier BV. - 0960-1481 .- 1879-0682. ; 162, s. 766-778
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Tidskriftsartikel (refereegranskat)abstract
- Airborne Wind Energy (AWE) is a new power technology that harvests wind energy at high altitudes using tethered wings. Studying the power potential of the system at a given location requires evaluating the local power production profile of the AWE system. As the optimal operational AWE system altitude depends on complex trade-offs, a commonly used technique is to formulate the power production computation as an Optimal Control Problem (OCP). In order to obtain an annual power production profile, this OCP has to be solved sequentially for the wind data for each time point. This can be computationally costly due to the highly nonlinear and complex AWE system model. This paper proposes a method how to reduce the computational effort when using an OCP for power computations of large-scale wind data. The method is based on homotopy-path-following strategies, which make use of the similarities between successively solved OCPs. Additionally, different machine learning regression models are evaluated to accurately predict the power production in the case of very large data sets. The methods are illustrated by computing a three-month power profile for an AWE drag-mode system. A significant reduction in computation time is observed, while maintaining good accuracy.
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| 8. |
- Malz, Elena, 1990, et al.
(författare)
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Drag-mode airborne wind energy vs. wind turbines: An analysis of power production, variability and geography
- 2020
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Ingår i: Energy. - : Elsevier BV. - 0360-5442 .- 1873-6785. ; 193
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Tidskriftsartikel (refereegranskat)abstract
- Airborne wind energy (AWE) is a wind power technology that harvests energy at high altitudes. The performance of AWE systems relative to traditional wind power turbines (WT) is of key relevance to any future commercialization. In particular, the power generation as well as its consistency over time will be key performance indicators. This study aims at identifying crucial factors that will influence the competitiveness of drag-mode AWE systems against WTs. To that end, the hourly power production of several drag-mode AWE designs is investigated using realistic wind data, and compared to the hourly power production of classical WTs. These results are then analyzed through three performance indicators: total annual power production, Gini coefficient, and correlation coefficient. The results show that AWE systems with multiple smaller wings have the highest annual production. The AWE power production of all AWE systems correlates in time at all sites with the production of WTs, and the Gini coefficients are similar. This observation challenges the belief that AWE systems will outcompete WTs thanks to a more consistent power output than WTs. However, the wing design as well as the local wind shear have a significant impact on the AWE performance.
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| 9. |
- Malz, Elena, 1990, et al.
(författare)
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The value of airborne wind energy to the electricity system
- 2022
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Ingår i: Wind Energy. - : Wiley. - 1099-1824 .- 1095-4244. ; 25:2, s. 281-299
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Tidskriftsartikel (refereegranskat)abstract
- Airborne wind energy (AWE) is a new power generation technology that harvests wind energy at high altitudes using tethered wings. The potentially higher energy yield, combined with expected lower costs compared to traditional wind turbines (WTs), motivates interest in further developing this technology. However, commercial systems are currently unavailable to provide more detailed information on costs and power generation. This study estimates the economic value of AWE in the future electricity system, and by that indicates which cost levels are required for AWE to be competitive. A specific focus is put on the relation between AWE systems (AWESs) and WTs. For this work, ERA-5 wind data are used to compute the power generation of the wind power technologies, which is implemented in a cost-minimizing electricity system model. By forcing a certain share of the annual electricity demand to be supplied by AWESs, the marginal system value (MSV) of AWE is investigated. The MSV is found to be affected by the AWE share, the wind resource, and the temporal distribution of the AWES's electricity generation. The MSV of AWE is location- and system-dependent and ranges between 1.4 and 2.2 (Formula presented.) at a low share of AWE supply (0%–30%). At higher shares, the MSV drops. The power generation of WTs and AWESs are related, implying that the wind technologies present a similar power source and can be used interchangeably. Thus, the introduction of AWESs will have a low impact on the cost-optimal wind power share in the electricity system, unless an AWES cost far below the system-specific MSV is attained.
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