LAPSE:2020.0249
Published Article
LAPSE:2020.0249
Optimal Control Algorithms with Adaptive Time-Mesh Refinement for Kite Power Systems
February 24, 2020
This article addresses the problem of optimizing electrical power generation using kite power systems (KPSs). KPSs are airborne wind energy systems that aim to harvest the power of strong and steady high-altitude winds. With the aim of maximizing the total energy produced in a given time interval, we numerically solve an optimal control problem and thereby obtain trajectories and controls for kites. Efficiently solving these optimal control problems is crucial when the results are used in real-time control schemes, such as model predictive control. For this highly nonlinear problem, we derive continuous-time models—in 2D and 3D—and implement an adaptive time-mesh refinement algorithm. By solving the optimal control problem with such an adaptive refinement strategy, we generate a block-structured adapted mesh which gives results as accurate as those computed using fine mesh, yet with much less computing effort and high savings in memory and computing time.
Keywords
adaptive algorithms, airborne wind energy, continuous-time systems, kite power systems, nonlinear systems, optimal control, real-time optimization, time-mesh refinement
Suggested Citation
Paiva LT, Fontes FACC. Optimal Control Algorithms with Adaptive Time-Mesh Refinement for Kite Power Systems. (2020). LAPSE:2020.0249
Author Affiliations
Paiva LT: SYSTEC–ISR, Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal; Instituto Superior de Engenharia do Porto, Politécnico do Porto, 4249-015 Porto, Portugal [ORCID]
Fontes FACC: SYSTEC–ISR, Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal [ORCID]
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Journal Name
Energies
Volume
11
Issue
3
Article Number
E475
Year
2018
Publication Date
2018-02-25
Published Version
ISSN
1996-1073
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Original Submission
Other Meta
PII: en11030475, Publication Type: Journal Article
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LAPSE:2020.0249
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doi:10.3390/en11030475
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Feb 24, 2020
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CC BY 4.0
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Feb 24, 2020
 
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Original Submitter
Calvin Tsay
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