IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i3p475-d133132.html
   My bibliography  Save this article

Optimal Control Algorithms with Adaptive Time-Mesh Refinement for Kite Power Systems

Author

Listed:
  • Luís Tiago Paiva

    (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
    Current address: Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal.)

  • Fernando A. C. C. Fontes

    (SYSTEC–ISR, Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal
    Current address: Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, Portugal.)

Abstract

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.

Suggested Citation

  • Luís Tiago Paiva & Fernando A. C. C. Fontes, 2018. "Optimal Control Algorithms with Adaptive Time-Mesh Refinement for Kite Power Systems," Energies, MDPI, vol. 11(3), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:475-:d:133132
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/3/475/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/3/475/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fernando A. C. C. Fontes & Hélène Frankowska, 2015. "Normality and Nondegeneracy for Optimal Control Problems with State Constraints," Journal of Optimization Theory and Applications, Springer, vol. 166(1), pages 115-136, July.
    2. Cherubini, Antonello & Papini, Andrea & Vertechy, Rocco & Fontana, Marco, 2015. "Airborne Wind Energy Systems: A review of the technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1461-1476.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali Arshad Uppal & Manuel C. R. M. Fernandes & Sérgio Vinha & Fernando A. C. C. Fontes, 2021. "Cascade Control of the Ground Station Module of an Airborne Wind Energy System," Energies, MDPI, vol. 14(24), pages 1-25, December.
    2. Manuel C. R. M. Fernandes & Sérgio Vinha & Luís Tiago Paiva & Fernando A. C. C. Fontes, 2022. "L 0 and L 1 Guidance and Path-Following Control for Airborne Wind Energy Systems," Energies, MDPI, vol. 15(4), pages 1-16, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ali, Qazi Shahzad & Kim, Man-Hoe, 2022. "Power conversion performance of airborne wind turbine under unsteady loads," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    2. Monica Motta & Caterina Sartori, 2020. "Normality and Nondegeneracy of the Maximum Principle in Optimal Impulsive Control Under State Constraints," Journal of Optimization Theory and Applications, Springer, vol. 185(1), pages 44-71, April.
    3. Johannes Alexander Müller & Mostafa Yasser Mostafa Khalil Elhashash & Volker Gollnick, 2022. "Electrical Launch Catapult and Landing Decelerator for Fixed-Wing Airborne Wind Energy Systems," Energies, MDPI, vol. 15(7), pages 1-19, March.
    4. Jochem De Schutter & Rachel Leuthold & Thilo Bronnenmeyer & Elena Malz & Sebastien Gros & Moritz Diehl, 2023. "AWEbox : An Optimal Control Framework for Single- and Multi-Aircraft Airborne Wind Energy Systems," Energies, MDPI, vol. 16(4), pages 1-32, February.
    5. Saleem, Arslan & Kim, Man-Hoe, 2020. "Aerodynamic performance optimization of an airfoil-based airborne wind turbine using genetic algorithm," Energy, Elsevier, vol. 203(C).
    6. Ali Arshad Uppal & Manuel C. R. M. Fernandes & Sérgio Vinha & Fernando A. C. C. Fontes, 2021. "Cascade Control of the Ground Station Module of an Airborne Wind Energy System," Energies, MDPI, vol. 14(24), pages 1-25, December.
    7. Trevisi, Filippo & McWilliam, Michael & Gaunaa, Mac, 2021. "Configuration optimization and global sensitivity analysis of Ground-Gen and Fly-Gen Airborne Wind Energy Systems," Renewable Energy, Elsevier, vol. 178(C), pages 385-402.
    8. Mostafa A. Rushdi & Ahmad A. Rushdi & Tarek N. Dief & Amr M. Halawa & Shigeo Yoshida & Roland Schmehl, 2020. "Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning," Energies, MDPI, vol. 13(9), pages 1-23, May.
    9. Malz, E.C. & Koenemann, J. & Sieberling, S. & Gros, S., 2019. "A reference model for airborne wind energy systems for optimization and control," Renewable Energy, Elsevier, vol. 140(C), pages 1004-1011.
    10. Iván Castro-Fernández & Ricardo Borobia-Moreno & Rauno Cavallaro & Gonzalo Sánchez-Arriaga, 2021. "Three-Dimensional Unsteady Aerodynamic Analysis of a Rigid-Framed Delta Kite Applied to Airborne Wind Energy," Energies, MDPI, vol. 14(23), pages 1-17, December.
    11. Mahdi Ebrahimi Salari & Joseph Coleman & Daniel Toal, 2018. "Power Control of Direct Interconnection Technique for Airborne Wind Energy Systems," Energies, MDPI, vol. 11(11), pages 1-17, November.
    12. Galym B. Teleuyev & Oksana V. Akulich & Marsel A. Kadyrov & Andrey A. Ponomarev & Elnur L. Hasanov, 2017. "Problems of Legal Regulation for Use and Development of Renewable Energy Sources in the Republic of Kazakhstan," International Journal of Energy Economics and Policy, Econjournals, vol. 7(5), pages 296-301.
    13. Gupta, Sowmya & Rajhans, Chinmay & Duttagupta, Siddhartha P. & Mitra, Mira, 2021. "Hybrid energy design for lighter than air systems," Renewable Energy, Elsevier, vol. 173(C), pages 781-794.
    14. Ali, Qazi Shahzad & Kim, Man-Hoe, 2021. "Design and performance analysis of an airborne wind turbine for high-altitude energy harvesting," Energy, Elsevier, vol. 230(C).
    15. André F. C. Pereira & João M. M. Sousa, 2022. "A Review on Crosswind Airborne Wind Energy Systems: Key Factors for a Design Choice," Energies, MDPI, vol. 16(1), pages 1-40, December.
    16. Malz, E.C. & Hedenus, F. & Göransson, L. & Verendel, V. & Gros, S., 2020. "Drag-mode airborne wind energy vs. wind turbines: An analysis of power production, variability and geography," Energy, Elsevier, vol. 193(C).
    17. Aram Arutyunov & Dmitry Karamzin, 2020. "A Survey on Regularity Conditions for State-Constrained Optimal Control Problems and the Non-degenerate Maximum Principle," Journal of Optimization Theory and Applications, Springer, vol. 184(3), pages 697-723, March.
    18. van der Vlugt, Rolf & Bley, Anna & Noom, Michael & Schmehl, Roland, 2019. "Quasi-steady model of a pumping kite power system," Renewable Energy, Elsevier, vol. 131(C), pages 83-99.
    19. Farhad Hasankhani & Amin Khademi, 2021. "Is it Time to Include Post‐Transplant Survival in Heart Transplantation Allocation Rules?," Production and Operations Management, Production and Operations Management Society, vol. 30(8), pages 2653-2671, August.
    20. Saleem, Arslan & Kim, Man-Hoe, 2019. "Performance of buoyant shell horizontal axis wind turbine under fluctuating yaw angles," Energy, Elsevier, vol. 169(C), pages 79-91.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:475-:d:133132. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.