Session: 07-04-02: Fluid Structure Interaction / Marine Electromechanical Systems and Ocean Mechatronics

Paper Number: 95804

95804 - Applying Artificial Intelligence to Optimize Small-Scale Ocean Current Turbine Performance 

Ocean currents offer a green, sustainable, and renewable energy resource to keep our environment invulnerable and clean. This paper presents a numerical study of a small scale three bladed horizontal axis underwater ocean current turbine (OCT) to detect autonomously the optimized rotational speed in RPM (revolutions per minute) for different current speeds to generate the maximum possible power. Ocean current circulates very similar to a conveyor belt, and the speeds of ocean currents are also changing over time. OCTs must be capable of operating independently without unscheduled maintenance. Thus, feedback control is the enabling technology for adjusting the turbine rotational speed in order to extract maximum power from hydrokinetic energy. Two different methods of numerical simulation have been developed to generate hydrokinetic loads such as torque, power and thrust for the OCT based on the geometry and design characteristics of the blades. Each blade is divided into 25 different cross sections from the FX77-W airfoil family. The first method is an in-house blade element momentum theory (BEM) algorithm which considers each cross section of the blade as a two-dimensional hydrofoil to calculate the local drag and lift coefficients for each sub-section to obtain the maximum generated power of the OCT. The second method uses computational fluid dynamics (CFD). ANSYS Fluent was used to estimate the moment, thrust and power of the turbine. The pressure-based Shear Stress Transport K-Omega (SST K-Omega 2 equation) was used for the solution. Many different generated power estimates based on these simulations have been conducted for different in-coming flow speeds in the range of few cm/s to as much as 4 m/s, along with varied turbine circular speeds. Subsequently, these estimates of generated power for different current speeds in addition to varied rotor blade rotational speeds, were provided as an input to an artificial neural network in order to forecast. The approach in this study was to ultimately predict the nominal rotor speed for a given in coming flow current to optimize the capability of the small scale OCT performance. The results of this numerical study will be used as one of the main sources of initial information for further research which is the design and implementation of an experimental small scale experimental ocean current turbine.  Ultimately, this will be conducted in the University of New Orleans towing tank. Also, the Results of the numerical study will be compared to the results of the experimental research.

Presenting Author: Shahab Rouhi The University of New Orleans

Presenting Author Biography: This is Shahab Rouhi, Ph.D. candidate in Engineering and Applied Science at the University of New Orleans, Naval Architecture and Marine Engineering Department. My main field is Engineering and Applied Science with the concentration on Electromechanical Systems. I have worked in collaboration with several different research groups during my post-graduate studies within the U.S. I have had an opportunity to develop a broad horizon in the field of electromechanical systems, renewable energy, and marine mechatronics. These investigations have been primarily concentrated on the Power Takeoff System Synthesis for Underwater Current Turbine which is a section of “Design and Control of Networked Offshore Hydrokinetic Power-Plants with Energy Storage” Founded by national science foundation (NSF). This cooperation is integrated research between University of New Orleans, Virginia Tech, and Florida Atlantic University in conjunction with Southeast National Marine Renewable Energy Center (SNMREC). As a Ph.D. student, I have started working on this promising project.<br/>I got my bachelor degree in Engineering in Tehran, Iran. Afterwards, I got my first M.Sc. degree in Integrated Science and Technology at the Southeastern Louisiana University in 2017. Subsequently, I started my second M.Sc. degree in Engineering and Applied Science at the University of New Orleans and I graduated in 2020. In addition, I have started my PhD studies in Engineering and Applied Science at the University of New Orleans.

Authors:

Shahab Rouhi The University of New Orleans
Setare Sadeqi The University of New Orleans
Nikolaos Xiros The University of New Orleans
Lothar Birk The University of New Orleans
Erdem Aktosun the University of New Orleans
Juliette Ioup The University of New Orleans