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Non-linear Model Predictive Control of Wave Energy Converters with Realistic Power Take-off Configurations and Loss Model

2019 IEEE Conference on Control Technology and Applications (CCTA)(2019)

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摘要
Model Predictive Control (MPC) has been recognized as a well-developed control strategy for optimizing the performance of wave energy converters (WECs). The standard problem involves maximizing the absorbed power from oncoming waves while respecting motion constraints of the device and force constraints of the power take-off (PTO). The generated electrical power is then calculated by assuming an ideal PTO with no power conversion losses or limitations to power flow. In this article, we remove the assumption of an ideal PTO and present four different control options that reflect unique combinations of PTO control and power flow constraints. We also recast the MPC problem to maximize the generated power instead of the absorbed power by accounting for the losses in the power train. Using a WEC with a hydraulic PTO, we develop a loss model suitable for controls optimization. Finally, we illustrate the process of setting up the non-linear MPC problem and compare the performance of competing control strategies using a common benchmark based on annual energy captured at a reference site.
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关键词
nonlinear model predictive control,wave energy converters,loss model,WEC,standard problem,motion constraints,force constraints,electrical power,power conversion losses,PTO control,power flow constraints,power train,hydraulic PTO,controls optimization,nonlinear MPC problem,annual energy,power take-off configurations
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