2024/10/14 by Kapil Khanal, Nate DeGoede, Khanal, Kapil +5
Computer Science · Engineering · Social Sciences · #Energy and Environmental Systems #FOS: Electrical engineering #Internet of Things and Social Network Interactions #Systems and Control (eess.SY) #Wave and Wind Energy Systems #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2410.11089
openalex publication_date 2024/10/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This study utilizes multidisciplinary design optimization (MDO) to design an array of heaving wave energy converters (WECs) for grid-scale energy production with decision variables and parameters chosen from the coupled disciplines of geometry, hydrodynamics, layout, motor-actuated reactive controls (with a force maximum constraint) and economics. We vary a WEC's dimensions, array layout, and control gain to minimize two objectives: the levelized cost of energy (LCOE) and the maximum separation distance. This multi-objective optimization approach results in a set of optimal design configurations that stakeholders can choose from for their specific application and needs. The framework yields a range of optimal (minimum) LCOE values from 0.21 to 0.23 $/kWh and a separation distance ranging from 97 to 62 meters. The WEC radius of 4m is found to be optimal, and the q-factor for optimal designs are greater than 1 up to 1.06 for a rhombus-like layout. Additionally, a post-optimality global sensitivity analysis of a design shows that wave heading, wave frequency, WEC lifetime, amplitude and interest rate accounts for most of the variance. Different designs in the Pareto set may be appealing for different decision makers based on their trade-off analysis. To that end, regression model is developed for design heuristics.