Multidisciplinary Design Optimization of Wave Energy Converter Farms Considering Uncertainty through Polynomial Chaos Expansion

Abstract

In this paper, a multidisciplinary design optimization problem under uncertainty is formulated for wave energy converter array. An array of heaving point absorbers for grid-scale energy production with decision variables and parameters chosen from the coupled disciplines of geometry, hydrodynamics, layout, and trajectory optimization thus resulting in a control co-design formulation of the plant and the control together. We study the benefits of MDO as applied to WEC farm layout optimization. We vary the wave energy converter (WEC) dimensions, array layout, and control gain to minimize the power per volume. Uncertainty in the electrical power is handled using regression based on polynomial chaos expansion (PCE) method at each design iteration. Traditional WEC farm design optimization approaches often neglect the multidisciplinary, coupled nature of WECs and the inherent uncertainty in ocean wave conditions and control responses. This leads to designs that may under perform in real-world environments. In this work, we address this limitation by incorporating uncertainty directly into the design optimization process using the technique of polynomial chaos expansion (PCE) to quantify the variability of the performance due to uncertain wave environment.