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Experimental Validation of Model Predictive Control Applied to the Azura Wave Energy Converter
Abstract
Ocean wave energy is a promising area of renewable energy development. However, there are unique operational challenges, particularly with regards to modeling, estimation, and control. Model Predictive Control (MPC) is a widely studied control approach that has strong potential for successful application to ocean wave energy conversion. It combines a predictive element, which is necessary for optimal wave energy conversion, along with consideration of system limitations, which is extremely important when operating within the very large forces present in ocean hydrodynamics. This paper presents MPC formulation and experimental testing, applied to the 1/15th scale Azura wave energy converter developed and tested by Northwest Energy Innovations (NWEI). Here, the results demonstrate successful prototype testing, with MPC providing an average increase in power production of 36% over standard fixed damping for six cases of sea states.
- Authors:
-
- Northwest Energy Innovations, Portland, OR (United States)
- Oregon State Univ., Corvallis, OR (United States)
- Publication Date:
- Research Org.:
- Northwest Energy Innovations, Portland, OR (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Water Power Technologies Office (EE-4WP)
- OSTI Identifier:
- 1581640
- Grant/Contract Number:
- EE0006923; EE0007693
- Resource Type:
- Accepted Manuscript
- Journal Name:
- IEEE Transactions on Sustainable Energy
- Additional Journal Information:
- Journal Name: IEEE Transactions on Sustainable Energy; Journal ID: ISSN 1949-3029
- Publisher:
- IEEE
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 16 TIDAL AND WAVE POWER; Renewable Energy sources; marine technology; ocean wave energy; model predictive control
Citation Formats
Ling, Bradley Adam, Bosma, Bret, and Brekken, Ted K. A. Experimental Validation of Model Predictive Control Applied to the Azura Wave Energy Converter. United States: N. p., 2019.
Web. doi:10.1109/TSTE.2019.2953868.
Ling, Bradley Adam, Bosma, Bret, & Brekken, Ted K. A. Experimental Validation of Model Predictive Control Applied to the Azura Wave Energy Converter. United States. doi:10.1109/TSTE.2019.2953868.
Ling, Bradley Adam, Bosma, Bret, and Brekken, Ted K. A. Mon .
"Experimental Validation of Model Predictive Control Applied to the Azura Wave Energy Converter". United States. doi:10.1109/TSTE.2019.2953868.
@article{osti_1581640,
title = {Experimental Validation of Model Predictive Control Applied to the Azura Wave Energy Converter},
author = {Ling, Bradley Adam and Bosma, Bret and Brekken, Ted K. A.},
abstractNote = {Ocean wave energy is a promising area of renewable energy development. However, there are unique operational challenges, particularly with regards to modeling, estimation, and control. Model Predictive Control (MPC) is a widely studied control approach that has strong potential for successful application to ocean wave energy conversion. It combines a predictive element, which is necessary for optimal wave energy conversion, along with consideration of system limitations, which is extremely important when operating within the very large forces present in ocean hydrodynamics. This paper presents MPC formulation and experimental testing, applied to the 1/15th scale Azura wave energy converter developed and tested by Northwest Energy Innovations (NWEI). Here, the results demonstrate successful prototype testing, with MPC providing an average increase in power production of 36% over standard fixed damping for six cases of sea states.},
doi = {10.1109/TSTE.2019.2953868},
journal = {IEEE Transactions on Sustainable Energy},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {11}
}
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