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Abstract A promising direction towards reducing the levelized cost of energy for wave energy converter (WEC) farms is to improve their performance. WEC design studies generally focus on a single design domain (e.g., geometry, control, or layout) to improve the farm’s performance under simplifying assumptions, such as regular waves. This strategy, however, has resulted in design recommendations that are impractical or limited in scope because WEC farms are complex systems that exhibit strong coupling among geometry, control, and layout domains. In addition, the location of the candidate site, which has a large impact on the performance of the farm, is often overlooked. Motivated by some of the limitations observed in WEC literature, this study uses an integrated design framework, based on simultaneous control co-design (CCD) principles, to discuss the impact of site selection and wave type on WEC farm design. Interactions among plant, control, and layout are also investigated and discussed using a wide range of simulations and optimization studies. All of the studies were conducted using frequency-domain heaving cylinder WEC devices within a farm with a linear reactive controller in the presence of irregular probabilistic waves. The results provide high-level guidelines to help the WEC design community move toward an integrated design perspective.
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This content will become publicly available on March 1, 2026
Concurrent geometry, control, and layout optimization of wave energy converter farms in probabilistic irregular waves using surrogate modeling
A promising direction toward improving the performance of wave energy converter (WEC) farms is to leverage a system-level integrated approach called control co-design (CCD), integrating geometric attributes, control parameters, and layout. However, the resulting optimization problem requires the estimation of hydrodynamic coefficients through computationally prohibitive numerical methods such as multiple scattering (MS). To mitigate this bottleneck, we construct data-driven surrogate models (SMs) using artificial neural networks and many-body expansion. To rectify errors in SMs, a hybrid optimization strategy, that involves solving an optimization problem with a genetic algorithm and SMs to generate a starting point which is then used by a gradient-based optimizer and MS, is devised. The effectiveness and efficiency of the proposed approach are demonstrated for a 5-WEC farm. For layout optimization study, the proposed framework offers a 91-fold increase in computational efficiency compared to the direct usage of MS. The framework also enables complex investigations, including concurrent geometry, control, and layout optimization of heaving cylindrical WEC devices in probabilistic irregular waves across various US coastal locations. The method’s scalability is assessed for a 25-WEC farm and the results indicate promising directions toward a practical framework for integrated WEC farm design with more tractable computational demands.
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- Award ID(s):
- 2034040
- PAR ID:
- 10566240
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Ocean Engineering
- Volume:
- 320
- Issue:
- C
- ISSN:
- 0029-8018
- Page Range / eLocation ID:
- 120183
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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