CFD-based Design Optimization of Ducted Hydrokinetic Turbines

TL;DR

This paper presents a CFD-based optimization of ducted hydrokinetic turbines, demonstrating that ducting can significantly improve energy extraction efficiency compared to unducted designs.

Contribution

The study introduces a gradient-based optimization framework using RANS and adjoint methods to design ducted turbines with enhanced efficiency.

Findings

Optimized ducted turbine achieves about 54% efficiency.

Efficiency surpasses typical unducted turbines like the Bahaj model.

Validation with higher-fidelity simulations confirms performance improvements.

Abstract

Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil fuels. It has been hypothesized that a duct can accelerate and condition the fluid flow passing the turbine blades, improving the overall energy extraction efficiency. However, no substantial evidence has been provided so far for hydrokinetic turbines. To investigate this problem, we perform a CFD-based optimization study with a blade-resolved Reynolds-averaged Navier--Stokes (RANS) solver to explore the design of a ducted hydrokinetic turbine that maximizes the efficiency of energy extraction. To handle the high-dimensional design space of the blade and duct geometry, we use a gradient-based optimization approach where the gradients are computed using the adjoint method. The final design is re-evaluated through higher-fidelity unsteady RANS (URANS) simulations. Our optimized ducted turbine achieves an efficiency of about 54% over a range of operating conditions, higher than the typical 46% efficiency of unducted turbines such as the well-known Bahaj model.