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.
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Control Co-Design of Mechanical Power Takeoff for a Dual-flap Surge Wave Energy Converter
Abstract—This paper presents a control co-design method for designing the mechanical power takeoff (PTO) system of a dual- flap oscillating surge wave energy converter. Unlike most existing work’s simplified representation of harvested power, this paper derives a more realistic electrical power representation based on a concise PTO modelling. This electrical power is used as the objective for PTO design optimization with energy maxi- mization control also taken into consideration to enable a more comprehensive design evaluation. A simple PI control structure speeds up the simultaneous co-optimization of control and PTO parameters, and an equivalent circuit model of the WEC not only streamlines power representation but also facilitates more insightful evaluation of the optimization results. The optimized PTO shows a large improvement in terms of power potential and actual power performance. It’s found the generator’s
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- Award ID(s):
- 2152694
- PAR ID:
- 10435895
- Date Published:
- Journal Name:
- 2023 OCEANS, IEEE
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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