Session A15: Energy: Water Power III

Ducted Hydrokinetic Turbine Design Optimization Using CFD-based Adjoint Method

Hydrokinetic turbines are designed to extract energy from different natural water sources, such as rivers or tidal and ocean currents. In order to improve the efficiency of energy extraction, a duct can be used to accelerate and condition the fluid flow passing across the turbine. In this work, we explore optimal design of a ducted hydrokinetic turbine to maximize the hydrodynamic efficiency, which is believed to exceed the Betz' limit (the theoretical limit derived from a bare turbine). For this purpose, we perform optimization on both the blade and duct geometries simultaneously using the CFD-based discrete adjoint method, implemented in an open-source environment DAFoam. The results will be discussed in terms of the maximum efficiency achieved and the effect of duct to turbine performance.   

Internal wave generation from ocean current turbine operation

Internal waves are formed when the turbulent wakes from submerged objects such as Ocean Current Turbines (OCT), collapse under a stable density stratification. The resulting waves can propagate in multiple directions, interact nonlinearly with other internal waves. In addition, OCT-generated internal waves will transport significant energy fluxes over large distances and produce substantial turbulent mixing when they break. We have developed numerical simulations to study the dynamic processes involved in the formation of internal waves from submerged OCT systems. Our investigation was expanded to include the effects of the Richardson number, and ambient turbulent intensity (TI), for OCTs operating in a stratified environment. Different density profiles were investigated, while turbines in the LES simulations were modeled using a Blade Element model. From the simulations, the critical bulk Richardson number for the formation of the IGWs was determined. Furthermore, by increasing the turbulent intensity, the formation of IGWs from OCT operation is enhanced.

This work was supported by the Coastal Studies Institute's North Carolina Renewable Ocean Energy Program.   

A Survey of Turbulence Characteristics at Six Tidal Energy Sites

The design and operation of hydrokinetic turbines that convert kinetic energy from tidal currents to electricity must account for the turbulence effects over a wide range of scales. Herein, we review and compare turbulence measurements collected with high-resolution acoustic Doppler velocimeters at half-a-dozen tidal energy sites worldwide to survey the range of turbulence characteristics observed. A consistent data collection, analysis, and reporting procedure are applied to allow an apple-to-apple comparison of turbulence metrics. This procedure could serve as an industry standard to guide the characterization of turbulence at tidal sites, focusing on turbulence intensity, turbulent kinetic energy, integral length scales, and velocity spectra and their distribution in the water profile and their temporal variation within the tidal cycle. Comparisons are made between the vertical distribution of normal Reynolds stresses from ADV measurements and those predicted using empirical models developed for developed turbulent boundary layers in open-channel flumes.    

Shape Optimization Methodology for Fluid Flows Using Mixed Variable Bayesian Optimization and Design-by-Morphing

Optimization of fluid flows and machinery is usually hampered by expensive cost functions and mixed variables, making common optimization or data driven techniques intractable. Furthermore, the design spaces for such problems are geometrically constrained. We present a novel methodology for optimization of fluid machinery by modifying the shape using Design-by-Morphing (DbM) and Bayesian optimization (BO), focusing on optimization of the shape of a draft tube for hydrokinetic turbine to increase its efficiency. DbM is a novel way of creating design spaces for the shape of objects by morphing baseline shapes, resulting in a large geometrically unconstrained design space. Bayesian optimization is useful for optimizing such large design spaces with expensive, noisy cost functions. However, mixed variable problems are a challenge for conventional BO techniques. Here, we introduce a novel 'Evolutionary Monte-Carlo Sampling' (EMCS) framework, a Bayesian optimization algorithm to handle mixed variable problems. Applying these two strategies in tandem, we demonstrate that we can optimize a geometrically unconstrained design space of a draft tube shape with minimum number of function calls. This methodology can be applied for the shape optimization for a multitude of fluid problems.   

Optimization of Offshore Wave Energy Harvester Using Reinforcement Learning

Wave energy has been of interest for its sustainability and high energy storing capability. However, the complexity of ocean waves caused by many environmental factors makes the harnessing process without sophisticated surface measurements difficult and inefficient.  In particular, most existing wave energy converter systems rely on static power take-off technologies, but active control of the power take-off (PTO) can enhance energy extraction. This project aims to utilize reinforcement learning to actively control a PTO damping coefficient to optimize the power over a specified time horizon with only one causal surface wave measurement.  It is achieved by integrating the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm with the PTO system of a two-body point absorber device. The algorithm learns the optimal damping coefficient based on the history of the time dynamics and limited knowledge of the future state based on the current wave detection sensor capabilities. The performance of the proposed control technology is tested for several wave energy concepts made up of multiple point absorbers.     

Performance and wake recovery of a tidal stream turbine under sheared inflow

Tidal Stream Turbine (TST) deployed at tidal energy sites is subjected to asymmetrical effects like sheared flow, which will lead to non-uniform loadings and unsteady performance, thus affecting the device survivability. In our present study, we focus on the wake propagation of a 1:20 scale TST model in a sheared, turbulent inflow that is generated using an active grid turbulence generator in the Tidal Turbulence Test facility (T³F) housed at Lehigh University. The near-wake velocity fields are measured with an acoustic Doppler velocimeter at three tip speed ratios to provide comprehensive wake characterization at various operating conditions. Wake data is collected along the depthwise direction in the center-line of the test section up to a downstream location of 4D. Important wake flow statistics, such as wake deficit, turbulence intensity, isotropic ratio, swirl number, and energy recovery, will be estimated and compared with a baseline case, named quasi-laminar case, which has a homogeneous inflow profile with a comparatively low turbulence intensity (~2.2%).   

Not Participating

Cross-flow turbines convert the kinetic power in wind and water currents to useful mechanical power. When individual cross-flow turbines or arrays of devices are deployed in real-world flows, some may be installed close to physical boundaries – for example, near the side of a building in an urban location, or next to the rocky wall of a tidal channel. Consequently, the turbine's blades will spend a portion of the rotation in close proximity to these boundaries, experiencing asymmetric confinement. Here, we experimentally investigate how the performance of a laboratory-scale cross-flow turbine changes with varying proximity to lateral boundaries.   

Modelling of the cavitation vortex rope in a Francis turbine at full-load conditions

Hydropower plants providing generation flexibility can experience several issues when operate in off-design conditions. In Francis turbines, the development of a cavitation vortex rope at the outlet of the runner may compromise the unit stability and prevent the operation. 

The vortex rope characteristics are influenced by the swirling flow at the outlet of the runner depending on the operating conditions. At full-load, the vortex rope may enter into an unstable regime causing vibrations in the whole hydraulic system.

The goal of this study is to investigate the volume and velocity field of the cavitation vortex rope at full-load, and to model these characteristics as a function of the operating parameters.

For this purpose, an experimental campaign has been performed on a reduced-scale model of a Francis turbine. A characterisation based on high-speed videos of the cavitation vortex rope has been implemented to estimate the cavitation volume variations at several full-load conditions. The reliability of the method is ensured by verifying the correlation between the computed volume, the pressure in the draft tube and the flow velocity field measured by Particle Image Velocimetry. This also allows studying the dynamics of the vortex to develop a predictive model of the flow stability.   

An oscillating cylinder with mechanically coupled rotation for energy harvesting

Flow-induced vibrations (FIV) of elastically mounted cylinders have been the subject of numerous studies, owing to their industrial relevance, especially in energy harvesting applications. Recent investigations focused on the amplification of the maximum vibration amplitude by combining such dynamics with forced rotation.

In this connection, we present a mechanical model consisting of a two-dimensional elastically mounted circular cylinder, immersed in an incompressible stream. The cylinder can undergo both vertical and rotational displacement. However, the rotation is mechanically connected to the translation through a pure rolling motion over a surface at distance R with respect to the cylinder center. This results in a single degree-of-freedom system governed by a forced second order oscillator equation. The forcing term comes from the numerical solution of the incompressible Navier-Stokes equations in which the interface condition is enforced by a direct forcing immersed boundary method.

We explore several working regimes of such device by spanning the parameter space defined by coupling radius R, solid-to-fluid mass ratio m*, and reduced freestream speed U*.