A report on state estimation for advanced control of wave energy converters (WECs), with supporting data models and slides from the overview presentation. The methods discussed are intended for use to enable real-time closed loop control of WECs.

This submission contains several papers, a final report, descriptions of a theoretical framework for two types of control systems, and descriptions of eight real-time flap load control policies with the objective of assessing the potential improvement of annual average capture efficiency at a reference site on an MHK device developed by Resolute Marine Energy, Inc. (RME). The submission also contains an LCOE model that estimates the performance and related energy cost improvements that each advanced control system might provide and recommendations for improving DOE's LCOE model. The two types of control systems are for wave energy converters which transform data into commands that, in the case of RME's OWSC wave energy converter, provide real-time adjustments to damping forces applied to the prime mover via the power take-off system (PTO). The control theories developed were: 1) Model Predictive Control (MPC) or so-called "non-causal" control whereby sensors deployed seaward of a wave energy converter measure incoming wave characteristics and transmit that information to a data processor which issues commands to the PTO to adjust the damping force to an optimal value; and 2) "Causal" control which utilizes local sensors on the wave energy converter itself to transmit information to a data processor which then issues appropriate commands to the PTO. The two advanced control policies developed by Scruggs and Re Vision were then compared to a simple control policy, Coulomb damping, which was utilized by RME during the two rounds of ocean trials it had conducted prior to the commencement of this project. The project work plan initially included a provision for RME to conduct hardware-in-the-loop (HIL) testing of the data processors and configurations of valves, sensors and rectifiers needed to implement the two advanced control systems developed by Scruggs and Re Vision Consulting but the funding for that aspect of the project was cut at the conclusion of Budget Period 1. Accordingly, more work needs to be done to determine: a) means and feasibility of implementing real-time control; and b) added costs associated with such implementation taking into account estimated effects on system availability in addition to component costs.

This is an LCOE (levelized cost of energy) baseline assessment for the Wave Carpet.

The over-arching project objective is to fully develop and validate optimal controls frameworks that can subsequently be applied widely to different WEC devices and concepts. Optimal controls of WEC devices represent a fundamental building block for WEC designers that must be considered as an integral part of every stage of device development. Using a building-blocks approach to optimal controls development, this effort will result in the full development of a feed-forward and feed-back control approach and a wave prediction system. Phase I focused primarily on numerical offline optimization and validation using wave tank testing of three industry partners? WEC devices, including CalWave, Ocean Energy, and Resolute Marine Energy. These industry partnerships allowed us to identify optimal control strategies for these different WEC topologies at different maturity levels. Phase II focused on demonstrating an integrated control system on a custom-built prototype for at-sea testing. A secondary focus during phase II is to adapt our systems identification, controls and wave-prediction frameworks to become more robust and comprehensive in respect to capability, robustness, and reliability. RE Vision Consulting leads this project and has compiled the final public domain report included in this submission.

Project baseline levelized cost of energy (LCOE) model for the Centipod WEC containing annual energy production (AEP) data, a cost breakdown structure (CBS), model documentation, and the LCOE content model. This baseline was built for comparison with the resultant LCOE model, built after implementation of the model predictive control (MPC) controller.

The objective of the project is to advance the Technology Readiness Level (TRL) of the Wave Energy Converter (WEC) developed by CalWave Wave Power Technologies Inc (CalWave) through advanced numerical simulations, dynamic hardware tests, and ultimately a scaled open water demonstration deployment while continuing to exceed DOE's target ACE threshold of 3m/M$. The outcomes of Budget Period 1 will be a detailed design of the scaled demonstration unit and bench testing of the critical hardware components.

The objective of the project is to advance the Technology Readiness Level (TRL) of the Wave Energy Converter (WEC) developed by CalWave Wave Power Technologies Inc (CalWave) through advanced numerical simulations, dynamic hardware tests, and ultimately a scaled open water demonstration deployment while continuing to exceed DOE's target ACE threshold of 3m/M$. The outcomes of Budget Period 1 will be a detailed design of the scaled demonstration unit and bench testing of the critical hardware components.

This archive contains the MATLAB code for the model predictive control (MPC) controller developed in this project. The archive containing the WaveDyn models used for analysis of the Centipod with the MPC controller is linked in this submission.

The work aims to achieve optimal tidal energy conversion through a comprehensive approach of modeling, optimization, and control hardware-in-the-loop (CHIL) validation. By developing accurate models and employing optimization techniques, it seeks to identify efficient system configurations and control strategies. HIL validation will ensure the performance and reliability of the optimized tidal energy conversion system. The preparation of the present manual has been supported by the U.S. Department of Energy.

This is the LCOE analysis spreadsheet and content model for the heaving point absorber buoy developed for controls purposes. The cost assessment was done on a wave-farm of 100-units.