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    • TEAMER: Experimental Validation and Analysis of Deep Reinforcement Learning Control for Wave Energy Converters

    Metadata Updated: June 17, 2025

    Through this TEAMER project, Michigan Technological University (MTU) collaborated with Oregon State University (OSU) to test the performance of a Deep Reinforcement Learning (DRL) control in the wave tank. Unlike model-based controls, DRL control is model-free and can directly maximize the performance of the Wave Energy Converter (WEC) in terms of power production, regardless of system complexity. While DRL control has demonstrated promising performance in previous studies, this project aimed to (1) evaluate the practical performance of DRL control and (2) identify the challenges and limitations associated with its practical implementation.

    To investigate the real-world performance of DRL-based control, the controller was trained with the LUPA numerical model using MATLAB/Simulink Deep Learning Toolbox and implemented on the Laboratory Upgrade Point Absorber (LUPA) device developed by the facility at OSU. A series of regular and irregular wave tests were conducted to evaluate the power harvested by the DRL control across different wave conditions, using various observation state selections, and incorporating a reward function that includes a penalty on the PTO force.

    The dataset consists of six main parts: (1) the Post Access Report (2) the test log containing the test ID, description, test data filename, wave data filename, wave condition, test notes for all conducted LUPA Testing Data (3) the tank testing results as described in the DRL Test Log (4) the model used for retraining the DRL control and associated results (5) the model used for pre-training the DRL control and associated results (6) the scripts used for processing the data (7) A readme file to indicate the folder contents and structure within the resources "LUPA Pretraining Data.zip", "LUPA Retraining Data.zip", and "ScriptsForPostProcessing.zip"

    This testing was funded by TEAMER RFTS 10 (request for technical support) program.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: Creative Commons Attribution

    Downloads & Resources

    Dates

    Metadata Created Date June 17, 2025
    Metadata Updated Date June 17, 2025

    Metadata Source

    Harvested from OpenEI data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date June 17, 2025
    Metadata Updated Date June 17, 2025
    Publisher Michigan Technological University
    Maintainer
    Identifier https://data.openei.org/submissions/8436
    Data First Published 2025-03-07T07:00:00Z
    Data Last Modified 2025-06-16T17:54:44Z
    Public Access Level public
    Bureau Code 019:20
    Metadata Context https://openei.org/data.json
    Metadata Catalog ID https://openei.org/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Data Quality True
    Harvest Object Id 2e7214fc-ff87-4e17-a2a6-b2a307ce601b
    Harvest Source Id 7cbf9085-0290-4e9f-bec1-91653baeddfd
    Harvest Source Title OpenEI data.json
    Homepage URL https://mhkdr.openei.org/submissions/628
    License https://creativecommons.org/licenses/by/4.0/
    Old Spatial {"type":"Polygon","coordinates":-180,-83,180,-83,180,83,-180,83,-180,-83}
    Program Code 019:009
    Projectlead Lauren Ruedy
    Projectnumber EE0008895
    Projecttitle Testing Expertise and Access for Marine Energy Research
    Source Datajson Identifier True
    Source Hash 87ea8f55a75644bbf2c955a2b22d9966fe3d01cac9afea2cb19132260674cb0e
    Source Schema Version 1.1
    Spatial {"type":"Polygon","coordinates":-180,-83,180,-83,180,83,-180,83,-180,-83}

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