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Wave energy converter control by wave prediction and dynamic programming

Author

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  • Li, Guang
  • Weiss, George
  • Mueller, Markus
  • Townley, Stuart
  • Belmont, Mike R.

Abstract

We demonstrate that deterministic sea wave prediction (DSWP) combined with constrained optimal control can dramatically improve the efficiency of sea wave energy converters (WECs), while maintaining their safe operation. We focus on a point absorber WEC employing a hydraulic/electric power take-off system. Maximizing energy take-off while minimizing the risk of damage is formulated as an optimal control problem with a disturbance input (the sea elevation) and with both state and input constraints. This optimal control problem is non-convex, which prevents us from using quadratic programming algorithms for the optimal solution. We demonstrate that the optimum can be achieved by bang–bang control. This paves the way to adopt a dynamic programming (DP) algorithm to resolve the on-line optimization problem efficiently. Simulation results show that this approach is very effective, yielding at least a two-fold increase in energy output as compared with control schemes which do not exploit DSWP. This level of improvement is possible even using relatively low precision DSWP over short time horizons. A key finding is that only about 1 second of prediction horizon is required, however, the technical difficulties involved in obtaining good estimates necessitate a DSWP system capable of prediction over tens of seconds.

Suggested Citation

  • Li, Guang & Weiss, George & Mueller, Markus & Townley, Stuart & Belmont, Mike R., 2012. "Wave energy converter control by wave prediction and dynamic programming," Renewable Energy, Elsevier, vol. 48(C), pages 392-403.
    • Handle: RePEc:eee:renene:v:48:y:2012:i:c:p:392-403
    DOI: 10.1016/j.renene.2012.05.003
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    References listed on IDEAS

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    1. Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
    2. Belmont, M.R., 2010. "Increases in the average power output of wave energy converters using quiescent period predictive control," Renewable Energy, Elsevier, vol. 35(12), pages 2812-2820.
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    Cited by:

    1. Ji, Xueyu & Shami, Elie Al & Monty, Jason & Wang, Xu, 2020. "Modelling of linear and non-linear two-body wave energy converters under regular and irregular wave conditions," Renewable Energy, Elsevier, vol. 147(P1), pages 487-501.
    2. Yetkin, Mertcan & Kalidoss, Sudharsan & Curtis, Frank E. & Snyder, Lawrence V. & Banerjee, Arindam, 2021. "Practical optimal control of a wave-energy converter in regular wave environments," Renewable Energy, Elsevier, vol. 171(C), pages 1382-1394.
    3. Zou, Shangyan & Song, Jiajun & Abdelkhalik, Ossama, 2023. "A sliding mode control for wave energy converters in presence of unknown noise and nonlinearities," Renewable Energy, Elsevier, vol. 202(C), pages 432-441.
    4. Li, Guang & Belmont, Mike R., 2014. "Model predictive control of sea wave energy converters – Part II: The case of an array of devices," Renewable Energy, Elsevier, vol. 68(C), pages 540-549.
    5. Tunde Aderinto & Hua Li, 2020. "Conceptual Design and Simulation of a Self-Adjustable Heaving Point Absorber Based Wave Energy Converter," Energies, MDPI, vol. 13(8), pages 1-15, April.
    6. Zou, Shangyan & Abdelkhalik, Ossama & Robinett, Rush & Bacelli, Giorgio & Wilson, David, 2017. "Optimal control of wave energy converters," Renewable Energy, Elsevier, vol. 103(C), pages 217-225.
    7. Zhang, Jincheng & Zhao, Xiaowei & Jin, Siya & Greaves, Deborah, 2022. "Phase-resolved real-time ocean wave prediction with quantified uncertainty based on variational Bayesian machine learning," Applied Energy, Elsevier, vol. 324(C).
    8. Li, Liang & Gao, Yan, 2023. "Development of a real-time wave energy control with consideration of control latency," Energy, Elsevier, vol. 277(C).
    9. Coe, Ryan G. & Bacelli, Giorgio & Forbush, Dominic, 2021. "A practical approach to wave energy modeling and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    10. Ekström, Rickard & Ekergård, Boel & Leijon, Mats, 2015. "Electrical damping of linear generators for wave energy converters—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 116-128.
    11. Li, Liang & Yuan, Zhiming & Gao, Yan, 2018. "Maximization of energy absorption for a wave energy converter using the deep machine learning," Energy, Elsevier, vol. 165(PA), pages 340-349.
    12. Yu, Shiwei & Gao, Siwei & sun, Han, 2016. "A dynamic programming model for environmental investment decision-making in coal mining," Applied Energy, Elsevier, vol. 166(C), pages 273-281.
    13. Liu, Ye & Wu, Xiaogang & Du, Jiuyu & Song, Ziyou & Wu, Guoliang, 2020. "Optimal sizing of a wind-energy storage system considering battery life," Renewable Energy, Elsevier, vol. 147(P1), pages 2470-2483.
    14. Shabara, Mohamed A. & Abdelkhalik, Ossama, 2023. "Dynamic modeling of the motions of variable-shape wave energy converters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    15. Chang, Grace & Jones, Craig A. & Roberts, Jesse D. & Neary, Vincent S., 2018. "A comprehensive evaluation of factors affecting the levelized cost of wave energy conversion projects," Renewable Energy, Elsevier, vol. 127(C), pages 344-354.
    16. 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.
    17. Ashton, I. & Van-Nieuwkoop-McCall, J.C.C. & Smith, H.C.M. & Johanning, L., 2014. "Spatial variability of waves within a marine energy site using in-situ measurements and a high resolution spectral wave model," Energy, Elsevier, vol. 66(C), pages 699-710.
    18. Burgaç, Alper & Yavuz, Hakan, 2019. "Fuzzy Logic based hybrid type control implementation of a heaving wave energy converter," Energy, Elsevier, vol. 170(C), pages 1202-1214.
    19. Hancheol Cho & Giorgio Bacelli & Ryan G. Coe, 2019. "Model Predictive Control Tuning by Inverse Matching for a Wave Energy Converter," Energies, MDPI, vol. 12(21), pages 1-18, October.
    20. Li, Guang & Belmont, Michael R., 2014. "Model predictive control of sea wave energy converters – Part I: A convex approach for the case of a single device," Renewable Energy, Elsevier, vol. 69(C), pages 453-463.

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