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

Anantha Karthikeyan1, Mirko Previsic2, Jeff Scruggs3, Allan Chertok4

  • 1ReVision Consulting
  • 2RE Vision Consulting
  • 3University of Michigan
  • 4Resolute Marine Energy

Details

16:10 - 16:30 | Mon 19 Aug | Lau, 5-205 | MoC3.3

Session: Renewable Energy Systems

Abstract

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. We also 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.