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A novel control method to maximize the energy-harvesting capability of an adjustable slope angle wave energy converter

Author

Listed:
  • Tri, Nguyen Minh
  • Truong, Dinh Quang
  • Thinh, Do Hoang
  • Binh, Phan Cong
  • Dung, Dang Tri
  • Lee, Seyoung
  • Park, Hyung Gyu
  • Ahn, Kyoung Kwan

Abstract

This paper introduces a novel control approach to maximizing the output energy of an adjustable slope angle wave energy converter (ASAWEC) with oil-hydraulic power take-off. Different from typical floating-buoy WECs, the ASAWEC is capable of capturing wave energy from both heave and surge modes of wave motions. For different waves, online determination of the titling angle plays a significant role in optimizing the overall efficiency of the ASAWEC. To enhance this task, the proposed method was developed based on a learning vector quantitative neural network (LVQNN) algorithm. First, the LVQNN-based supervisor controller detects wave conditions and directly produces the optimal titling angles. Second, a so-called efficiency optimization mechanism (EOM) with a secondary controller was designed to regulate automatically the ASAWEC slope angle to the desired value sent from the supervisor controller. A prototype of the ASAWEC was fabricated and a series of simulations and experiments was performed to train the supervisor controller and validate the effectiveness of the proposed control approach with regular waves. The results indicated that the system could reach the optimal angle within 2s and subsequently, the output energy could be maximized. Compared to the performance of a system with a vertically fixed slope angle, an increase of 5% in the overall efficiency was achieved. In addition, simulations of the controlled system were performed with irregular waves to confirm the applicability of the proposed approach in practice.

Suggested Citation

  • Tri, Nguyen Minh & Truong, Dinh Quang & Thinh, Do Hoang & Binh, Phan Cong & Dung, Dang Tri & Lee, Seyoung & Park, Hyung Gyu & Ahn, Kyoung Kwan, 2016. "A novel control method to maximize the energy-harvesting capability of an adjustable slope angle wave energy converter," Renewable Energy, Elsevier, vol. 97(C), pages 518-531.
    • Handle: RePEc:eee:renene:v:97:y:2016:i:c:p:518-531
    DOI: 10.1016/j.renene.2016.05.092
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    References listed on IDEAS

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    1. Truong, Dinh Quang & Ahn, Kyoung Kwan, 2014. "Development of a novel point absorber in heave for wave energy conversion," Renewable Energy, Elsevier, vol. 65(C), pages 183-191.
    2. Sheng, Wanan & Alcorn, Raymond & Lewis, Anthony, 2015. "On improving wave energy conversion, part I: Optimal and control technologies," Renewable Energy, Elsevier, vol. 75(C), pages 922-934.
    3. Cuadra, L. & Salcedo-Sanz, S. & Nieto-Borge, J.C. & Alexandre, E. & Rodríguez, G., 2016. "Computational intelligence in wave energy: Comprehensive review and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1223-1246.
    4. Heikkinen, Heidi & Lampinen, Markku J. & Böling, Jari, 2013. "Analytical study of the interaction between waves and cylindrical wave energy converters oscillating in two modes," Renewable Energy, Elsevier, vol. 50(C), pages 150-160.
    5. Sheng, Wanan & Alcorn, Raymond & Lewis, Anthony, 2015. "On improving wave energy conversion, part II: Development of latching control technologies," Renewable Energy, Elsevier, vol. 75(C), pages 935-944.
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    Cited by:

    1. 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.
    2. Mohd Afifi Jusoh & Mohd Zamri Ibrahim & Muhamad Zalani Daud & Aliashim Albani & Zulkifli Mohd Yusop, 2019. "Hydraulic Power Take-Off Concepts for Wave Energy Conversion System: A Review," Energies, MDPI, vol. 12(23), pages 1-23, November.
    3. Wang, Liguo & Isberg, Jan & Tedeschi, Elisabetta, 2018. "Review of control strategies for wave energy conversion systems and their validation: the wave-to-wire approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 366-379.
    4. Naga Kavitha Kommuri & Andrew McGordon & Antony Allen & Dinh Quang Truong, 2022. "A Novel Adaptive Equivalence Fuel Consumption Minimisation Strategy for a Hybrid Electric Two-Wheeler," Energies, MDPI, vol. 15(9), pages 1-19, April.

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