IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v204y2020ics0360544220309889.html
   My bibliography  Save this article

Maximization of wave power extraction of a heave point absorber with a sea-state-based causal control algorithm

Author

Listed:
  • Li, Liang
  • Gao, Zhen

Abstract

A causal control strategy is developed to tackle the non-causality arising in the real-time implementation of optimal wave energy control. The proposed control strategy utilizes a causal approximation transfer function to link the current wave force to the desired buoy velocity so as to eliminate the non-causality. An optimum model of the approximation transfer function is derived considering the power density distribution of the local wave spectrum. Based on the optimized approximation transfer function, the desired buoy velocity is achieved by tuning the power take-off mechanical force with the PID control. The efficiency of the proposed causal control strategy is assessed for a heaving point-absorber, in a set of random wave conditions. Generally, the heaving point-absorber could extract wave power up to 90% of the theoretical upper bound using the proposed control strategy. The sensitivity of the proposed control to viscous damping effect due to drag and wave spectrum bandwidth is investigated. Although it is less efficient in broad-banded sea state, the control efficiency is still within an acceptable level (above 70%).

Suggested Citation

  • Li, Liang & Gao, Zhen, 2020. "Maximization of wave power extraction of a heave point absorber with a sea-state-based causal control algorithm," Energy, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:energy:v:204:y:2020:i:c:s0360544220309889
    DOI: 10.1016/j.energy.2020.117881
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220309889
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.117881?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Truong, D.Q. & Ahn, K.K., 2012. "Wave prediction based on a modified grey model MGM(1,1) for real-time control of wave energy converters in irregular waves," Renewable Energy, Elsevier, vol. 43(C), pages 242-255.
    2. Henriques, J.C.C. & Gato, L.M.C. & Falcão, A.F.O. & Robles, E. & Faÿ, F.-X., 2016. "Latching control of a floating oscillating-water-column wave energy converter," Renewable Energy, Elsevier, vol. 90(C), pages 229-241.
    3. Zhang, Xiantao & Tian, Xinliang & Xiao, Longfei & Li, Xin & Chen, Lifen, 2018. "Application of an adaptive bistable power capture mechanism to a point absorber wave energy converter," Applied Energy, Elsevier, vol. 228(C), pages 450-467.
    4. Penalba, Markel & Ringwood, John V., 2019. "A high-fidelity wave-to-wire model for wave energy converters," Renewable Energy, Elsevier, vol. 134(C), pages 367-378.
    5. Li, Liang & Liu, Yuanchuan & Yuan, Zhiming & Gao, Yan, 2018. "Wind field effect on the power generation and aerodynamic performance of offshore floating wind turbines," Energy, Elsevier, vol. 157(C), pages 379-390.
    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. Li, L. & Gao, Y. & Ning, D.Z. & Yuan, Z.M., 2021. "Development of a constraint non-causal wave energy control algorithm based on artificial intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).

    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. Nicola Delmonte & Eider Robles & Paolo Cova & Francesco Giuliani & François Xavier Faÿ & Joseba Lopez & Piero Ruol & Luca Martinelli, 2020. "An Iterative Refining Approach to Design the Control of Wave Energy Converters with Numerical Modeling and Scaled HIL Testing," Energies, MDPI, vol. 13(10), pages 1-19, May.
    2. Li, Liang & Gao, Yan, 2023. "Development of a real-time wave energy control with consideration of control latency," Energy, Elsevier, vol. 277(C).
    3. Zhigang Liu & Wei Huang & Shi Liu & Xiaomei Wu & Chun Sing Lai & Yi Yang, 2023. "An Improved Hydraulic Energy Storage Wave Power-Generation System Based on QPR Control," Energies, MDPI, vol. 16(2), pages 1-18, January.
    4. Yao, Ganzhou & Luo, Zirong & Lu, Zhongyue & Wang, Mangkuan & Shang, Jianzhong & Guerrerob, Josep M., 2023. "Unlocking the potential of wave energy conversion: A comprehensive evaluation of advanced maximum power point tracking techniques and hybrid strategies for sustainable energy harvesting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 185(C).
    5. Qiao Li & Motohiko Murai & Syu Kuwada, 2018. "A Study on Electrical Power for Multiple Linear Wave Energy Converter Considering the Interaction Effect," Energies, MDPI, vol. 11(11), pages 1-20, November.
    6. Wang, Mangkuan & Shang, Jianzhong & Luo, Zirong & Lu, Zhongyue & Yao, Ganzhou, 2023. "Theoretical and numerical studies on improving absorption power of multi-body wave energy convert device with nonlinear bistable structure," Energy, Elsevier, vol. 282(C).
    7. Hayrettin Bora Karayaka & Yi-Hsiang Yu & Eduard Muljadi, 2021. "Investigations into Balancing Peak-to-Average Power Ratio and Mean Power Extraction for a Two-Body Point-Absorber Wave Energy Converter," Energies, MDPI, vol. 14(12), pages 1-24, June.
    8. Luana Gurnari & Pasquale G. F. Filianoti & Marco Torresi & Sergio M. Camporeale, 2020. "The Wave-to-Wire Energy Conversion Process for a Fixed U-OWC Device," Energies, MDPI, vol. 13(1), pages 1-25, January.
    9. Wen, Binrong & Jiang, Zhihao & Li, Zhanwei & Peng, Zhike & Dong, Xingjian & Tian, Xinliang, 2022. "On the aerodynamic loading effect of a model Spar-type floating wind turbine: An experimental study," Renewable Energy, Elsevier, vol. 184(C), pages 306-319.
    10. Zhou, Yang & Xiao, Qing & Liu, Yuanchuan & Incecik, Atilla & Peyrard, Christophe & Wan, Decheng & Pan, Guang & Li, Sunwei, 2022. "Exploring inflow wind condition on floating offshore wind turbine aerodynamic characterisation and platform motion prediction using blade resolved CFD simulation," Renewable Energy, Elsevier, vol. 182(C), pages 1060-1079.
    11. Correia da Fonseca, F.X. & Gomes, R.P.F. & Henriques, J.C.C. & Gato, L.M.C. & Falcão, A.F.O., 2016. "Model testing of an oscillating water column spar-buoy wave energy converter isolated and in array: Motions and mooring forces," Energy, Elsevier, vol. 112(C), pages 1207-1218.
    12. Bao, Jian & Yu, Dingyong, 2024. "Hydrodynamic performance optimization of a cost-effective WEC-type floating breakwater with half-airfoil bottom," Renewable Energy, Elsevier, vol. 226(C).
    13. Xinyu Han & Rongrong Li, 2019. "Comparison of Forecasting Energy Consumption in East Africa Using the MGM, NMGM, MGM-ARIMA, and NMGM-ARIMA Model," Energies, MDPI, vol. 12(17), pages 1-24, August.
    14. Ozkop, Emre & Altas, Ismail H., 2017. "Control, power and electrical components in wave energy conversion systems: A review of the technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 106-115.
    15. Xiao, Han & Wang, Xu, 2024. "Sensitivity analysis of design parameters and their interactions and performance prediction of a novel twin turbine wave energy converter," Energy, Elsevier, vol. 293(C).
    16. Zhang, Haicheng & Xi, Ru & Xu, Daolin & Wang, Kai & Shi, Qijia & Zhao, Huai & Wu, Bo, 2019. "Efficiency enhancement of a point wave energy converter with a magnetic bistable mechanism," Energy, Elsevier, vol. 181(C), pages 1152-1165.
    17. Elhanafi, Ahmed & Kim, Chan Joo, 2018. "Experimental and numerical investigation on wave height and power take–off damping effects on the hydrodynamic performance of an offshore–stationary OWC wave energy converter," Renewable Energy, Elsevier, vol. 125(C), pages 518-528.
    18. Silva, Jorge Marques & Vieira, Susana M. & Valério, Duarte & Henriques, João C.C., 2023. "GA-optimized inverse fuzzy model control of OWC wave power plants," Renewable Energy, Elsevier, vol. 204(C), pages 556-568.
    19. Wang, Yingguang & Wang, Lifu, 2018. "Towards realistically predicting the power outputs of wave energy converters: Nonlinear simulation," Energy, Elsevier, vol. 144(C), pages 120-128.
    20. Nana Geng & Yong Zhang & Yixiang Sun & Yunjian Jiang & Dandan Chen, 2015. "Forecasting China’s Annual Biofuel Production Using an Improved Grey Model," Energies, MDPI, vol. 8(10), pages 1-20, October.

    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:eee:energy:v:204:y:2020:i:c:s0360544220309889. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.