Signature Projects are intended to bring focus to a selection of U.S. Department of Energy's Water Power Technologies Office (WPTO) projects. By designating a Signature Project, the project reports, datasets, and associated papers can be easily discoverable. By bringing together all aspects of a project, whether a completed legacy project or an ongoing investigation, the MRE community can be informed of what investigations have been undertaken, which have succeeded, what tools are available, and where gaps in information persist.
Advanced WEC Dynamics & Controls
Sandia National Laboratories’ Advanced WEC (Wave Energy Converter) Dynamics and Controls project sought to leverage control design and dynamics modeling to improve the performance of WECs.
Numerous studies have shown that advanced control of a wave energy converter power take off can provide significant increases (on the order of 200-300%) in WEC energy absorption. These increases can in turn lead to reductions in levelized cost of energy (LCOE), both through the increases in energy generation, but also by decreasing loading. Sandia’s Advanced WEC Dynamics and Controls project focused on transitioning control design approaches from simplified paper studies to application in full-scale devices. By leveraging a wide range of dynamics and controls, robotics, modeling, and testing expertise, the project delivered on this goal, producing broad dissemination products (webinars, workshops, journal and conference papers, and open-source data sets) and direct benefit to individual WEC developers through numerous industry collaboration projects.
The Advanced WEC Dynamics and Controls project originally started with the goal to design a "plug-and-play" controller to realize the benefits in terms of performance that researchers had shown could be attributed to control systems, such as the great improvement in power absorption. According to the original approach, most of the effort would have been spent on bringing to bare nonlinear modeling/control and other highly-focused efforts on the problem. After the initial simulation work conducted to provide a comparison of control systems for WECs, and during the design stages of the "WaveBot" device that was tested at the Navy's Maneuvering and Sea Keeping (MASK) basin (Coe et al. 2016, Coe et al. 2018, Coe et al. 2019), it became evident that a more fundamental understanding of the problem was necessary.
While the concept of optimal WEC control and dynamics existed, there was a lack of understanding about the implications of control concepts for overall device design. In the case of ships and wind turbines, the control system can be designed separately, once the design of the device has been finalized, because the controller is only concerned with the quasi-steady state conditions of the device (mean rotor speed and pitch angle for wind turbines, orientation of a ship), that is the slow dynamics, and it does not have to interact or compensate with the disturbance.
With this realization, much of the project's work became integration of knowledge from disparate sources. The scope was effectively broadened to become understanding the overall dynamics, and the product became a tractable workflow for designing, modeling, and testing WEC controllers with readily available components and methods, with particular regard to the immense literature and tools available from classical control theory and practice. This has been done by shifting the point of view when looking at WECs from a mainly hydrodynamic focused approach to a more dynamics and control oriented framework, by starting to use classical control tools, such as block diagrams and Bode plots. Additionally, we have studied and documented in depth the practical aspects of implementing a control system on a real device, such as closed loop stability analysis; a fundamental requirement that had been previously overlooked. As a consequence of this work, we have developed an initial framework that will enable control co-design of WECs (power take-off systems, hulls, mooring systems, power electronics, etc.). At this stage, the focus of this project team has further pivoted to transferring knowledge to developers and academia through direct and indirect collaborations and dissemination of data, reports, and peer-reviewed scientific publication.
The project's findings can be summarized as follows:
System identification (SID) (Bacelli and Coe 2017, Bacelli et al. 2017, Coe et al. 2016): To perform experimental tests of a WEC and obtain empirical models, the methods that are preferred in fields such as aerospace, automotive, and electronic engineering are equally powerful for testing WECs. Based on the wealth of knowledge on the topic of SID, wave tank tests should be using multi-sine signals that repeat to provide noise cancellation. Model fitting and data processing techniques utilizing the frequency domain are both powerful and well-suited to WECs.
PTO design and bench testing (Bacelli et al. 2017, Bacelli et al. 2019): Given the critical role played by the PTO, the design and testing of these systems must be given focused attention. The principles practiced in robotics design, where closed-loop performance must also be considered, offer a wealth of guidance for WEC PTO design. Additionally, testing PTO hardware, using hardware-in-theloop (HIL) and rapid prototyping experiments, is essential to understanding the dynamics and efficiency of such systems.
Local linear models (Cho et al. 2018): While the physics of a WEC system are indeed nonlinear, the nature of operation and the slowly changing nature of the ocean sea states enables the usage of local linear models. This approach is both simpler and also enables the usage of a large suite of tools and methods. The drawback of this approach is the neglect of what turns out to be a very small amount of power.
Band-limited controller design (Nevarez et al. 2018, Coe et al. 2018, Bacelli and Coe 2020): By acknowledging the band-limited nature of real ocean waves, the maximum power transfer problem for WEC control can be simplified greatly. For the WaveBot device studied in this project, a simple PI controller can achieve roughly 80% of the optimal power absorption. A higher-order feedback controller can achieve 93% of the optimal.
Integrated WEC impedance model (Bacelli and Coe 2020, Coe et al. 2019): By utilizing a multiport framework, the dynamics of various WEC subsystems (hydrodynamics, drivetrain, generator, transmission system) can be integrated into a single impedance model, allowing both for control design that considers the entire WEC system as well as control co-design of the entire WEC system.