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Techno-economic optimization of a wave energy converter array in front of a vertical seawall with artificial neural networks

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  • Natarajan, Senthil Kumar
  • Cho, Il Hyoung

Abstract

Techno-economic optimization is crucial in the early development of wave energy converters (WECs) to ensure economic viability by evaluating technical performance and cost. This study optimizes a WEC array in both inline and staggered configurations in front of a vertical seawall under irregular wave conditions, considering variations in WEC diameter, WEC spacing, row distance, and wave incidence angles. The WECs use vertical cylindrical floaters oscillating independently in heave, with other motions constrained. Hydrodynamic analyses employ the WAMIT code based on linear potential theory, incorporating the seawall's influence through the method of image. Artificial neural network (ANN) models are employed to optimize the WEC spacing and row distance for inline and staggered configurations, respectively. Techno-economic optimization utilizes three techno-economic metrics: the ratio of WEC submerged volume to extracted power and two newly introduced metrics, the ratios of indicative array footprint to extracted power and indicative array width to extracted power, to identify cost-efficient configurations. The analysis identifies that inline configurations are preferable when costs are driven by WEC capital and nearshore area, while staggered configurations are more cost-effective when nearshore width is the primary consideration. The new metrics enhance the techno-economic optimization process, enabling a more comprehensive and scalable approach.

Suggested Citation

  • Natarajan, Senthil Kumar & Cho, Il Hyoung, 2026. "Techno-economic optimization of a wave energy converter array in front of a vertical seawall with artificial neural networks," Energy, Elsevier, vol. 342(C).
    • Handle: RePEc:eee:energy:v:342:y:2026:i:c:s0360544225052892
    DOI: 10.1016/j.energy.2025.139647
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    References listed on IDEAS

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