Development of a Control Co-Design Modeling Tool for Marine Hydrokinetic Turbines: Preprint

Hannah Ross, Matthew Hall, Daniel Herber, Jason Jonkman, Athul Krishna Sundarrajan, Thanh Toan Tran, Alan Wright, Daniel Zalkind, Nick Johnson

Research output: Contribution to conferencePaper


This report describes the ongoing and planned development of the software package CT-Opt (Current/Tidal Optimization), a control co-design modeling tool for marine hydrokinetic turbines. The commercialization of these turbines has faced significant challenges due to the complex, multidisciplinary nature of their design and the extreme environmental conditions of their operation. This project aims to create a modeling tool that will enable the efficient design of robust, cost-competitive hydrokinetic turbine systems. Rather than using traditional optimization methods, CT-Opt combines multiple models across a range of fidelities to enable coupled optimization of the system design and system controller via a control co-design approach. With this method, the parameters that affect system performance are considered more comprehensively at every stage of the design process. The lowest-fidelity, frequency-domain model called by CT-Opt is RAFT (Response Amplitudes of Floating Turbines), which was originally developed by the National Renewable Energy Laboratory (NREL) to model response amplitudes of floating offshore wind turbines. The highest-fidelity, time-domain model is OpenFAST, which was developed by NREL for land-based and offshore wind turbines. As part of the CT-Opt project, new functionalities will be added to RAFT and OpenFAST to enable the accurate simulation of fixed and floating marine hydrokinetic turbines. In addition to expanding the capabilities of RAFT and OpenFAST, new midfidelity models will be developed. These models will be based on RAFT and OpenFAST and will consist of linearized, state-space models derived from the fully coupled, nonlinear OpenFAST equations and derivative function surrogate models that approximate the nonlinear system behavior. Each model will be coupled with controllers to allow control co-design methods to be applied both within models and across fidelity levels, enabling efficient system optimization.
Original languageAmerican English
Number of pages13
StatePublished - 2022
EventASME 2022 International Mechanical Engineering Congress and Exposition (IMECE2022) - Columbus, Ohio
Duration: 30 Oct 20223 Nov 2022


ConferenceASME 2022 International Mechanical Engineering Congress and Exposition (IMECE2022)
CityColumbus, Ohio

NREL Publication Number

  • NREL/CP-5700-82561


  • control co-design
  • design optimization
  • marine renewable energy
  • marine turbines
  • surrogate modeling


Dive into the research topics of 'Development of a Control Co-Design Modeling Tool for Marine Hydrokinetic Turbines: Preprint'. Together they form a unique fingerprint.

Cite this