Energy Capturing Prediction in the Integrated Hydrodynamic-Electromechanical Modelling of Tidal Turbines

Research activity on the integrated hydrodynamic and electro-mechanical analysis of hydrokinetic turbines at the Italian Institute for Marine Engineering is presented. The computational methodology includes the interaction between rotor hydrodynamics, drivetrain dynamics, mechanical to electrical power conversion, and control strategies. The objective is to obtain a computationally-efficient simulation framework, where reliable predictions of turbine response under real operating conditions in tidal sites and rivers are obtained at limited computing costs.Preliminary results of the ongoing activity are presented to give an overview of the problems that can be studied in the tidal energy sector. This includes the evaluation of the hydrodynamic performance of an existing turbine, or the design of a newbuild device with given performance objectives and operational constraints. The energy output in a real tidal site can be obtained by a simple definition of the flow characteristics in the site. Furthermore, the integrated hydrodynamic/electro-mechanical model provides a support tool for the preliminary design of the turbine power take-off system, and allows to investigate the performance of alternative control strategies for turbine operation in highly-variable onset flow conditions.The activity is the subject of an ongoing collaboration with the Chinese Changchun Institute of Technology. Knowledge sharing and data exchange is focused on the development of innovative solutions to design high-performance turbines for sites characterized by relatively low intensity of the tidal stream velocity.

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Publication Details

Published
2025-07-18
DOI
https://doi.org/10.1109/icceee63357.2025.11156927
Primary Topic
Wind Energy Research and Development
Type
article
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Energy Capturing Prediction in the Integrated Hydrodynamic-Electromechanical Modelling of Tidal Turbines

Mohammad Hossein Rafiei, Wenzhou Liu, Yilong Yang, Lixin Pei et al.
Wind Energy Research and Development
article

Energy Capturing Prediction in the Integrated Hydrodynamic-Electromechanical Modelling of Tidal Turbines

Mohammad Hossein Rafiei, Wenzhou Liu, Yilong Yang, Lixin Pei, Francesco Salvatore, Mona Shayeghan
article en

Abstract

Research activity on the integrated hydrodynamic and electro-mechanical analysis of hydrokinetic turbines at the Italian Institute for Marine Engineering is presented. The computational methodology includes the interaction between rotor hydrodynamics, drivetrain dynamics, mechanical to electrical power conversion, and control strategies. The objective is to obtain a computationally-efficient simulation framework, where reliable predictions of turbine response under real operating conditions in tidal sites and rivers are obtained at limited computing costs.Preliminary results of the ongoing activity are presented to give an overview of the problems that can be studied in the tidal energy sector. This includes the evaluation of the hydrodynamic performance of an existing turbine, or the design of a newbuild device with given performance objectives and operational constraints. The energy output in a real tidal site can be obtained by a simple definition of the flow characteristics in the site. Furthermore, the integrated hydrodynamic/electro-mechanical model provides a support tool for the preliminary design of the turbine power take-off system, and allows to investigate the performance of alternative control strategies for turbine operation in highly-variable onset flow conditions.The activity is the subject of an ongoing collaboration with the Chinese Changchun Institute of Technology. Knowledge sharing and data exchange is focused on the development of innovative solutions to design high-performance turbines for sites characterized by relatively low intensity of the tidal stream velocity.

Roma Tre University (IT), Institute of Marine Engineering (IT), Changchun Institute of Technology (CN), National Research Council (IT)
Openalex Percentile: Top 67%
Wind Energy Research and Development
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