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  • Concurrent Probabilistic Control Co-Design and Layout Optimization of Wave Energy Converter Farms Using Surrogate Modeling
Title: Concurrent Probabilistic Control Co-Design and Layout Optimization of Wave Energy Converter Farms Using Surrogate Modeling
Wave energy converters (WECs) are a promising candidate for meeting the increasing energy demands of today’s society. It is known that the sizing and power take-off (PTO) control of WEC devices have a major impact on their performance. In addition, to improve power generation, WECs must be optimally deployed within a farm. While such individual aspects have been investigated for various WECs, potential improvements may be attained by leveraging an integrated, system-level design approach that considers all of these aspects. However, the computational complexity of estimating the hydrodynamic interaction effects significantly increases for large numbers of WECs. In this article, we undertake this challenge by developing data-driven surrogate models using artificial neural networks and the principles of many-body expansion. The effectiveness of this approach is demonstrated by solving a concurrent plant (i.e., sizing), control (i.e., PTO parameters), and layout optimization of heaving cylinder WEC devices. WEC dynamics were modeled in the frequency domain, subject to probabilistic incident waves with farms of 3, 5, 7, and 10 WECs. The results indicate promising directions toward a practical framework for array design investigations with more tractable computational demands.  more » « less
Award ID(s):
2034040
PAR ID:
10479668
Author(s) / Creator(s):
;
Publisher / Repository:
American Society of Mechanical Engineers
Date Published:
Journal Name:
ASME 2023 International Design Engineering Technical Conferences
ISBN:
978-0-7918-8731-8
Format(s):
Medium: X
Location:
Boston, Massachusetts, USA
Sponsoring Org:
National Science Foundation
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