Renewable energy sources can be a solution for the recent pollution increasing scenario and the need for diversification of the energy market. Among such alternative sources,wave energy represents a viable solution, due to the its high power density and accessibility.Nonetheless, wave energy is still in phase of development, and a key stepping stone towards commercialisation is strongly linked to the availability of optimal control strategies for maximum energy harvesting. With its ability to handle system constraints and optimise power absorption directly, model predictive control (MPC) has gained popularity within the WEC community as a potential solution for the corresponding energy-maximising problem. In this study, an MPC strategy is developed for real-time control of the so-called PeWEC energy harvesting system,providing also a solution for the wave excitation estimation and forecasting problem, inherently required by the MPC controller to achieve optimal performance. Improved computational requirements are obtained via definition of a reduced control-oriented model, describing the dynamics of the system in a compact form. The performance of the proposed strategy is illustrated via a comprehensive numerical appraisal.
Energy-maximising model predictive control for a multi degree-of-freedom pendulum-based wave energy system / Papini, G.; Pasta, E.; Carapellese, F.; Bonfanti, M.. - 55:(2022), pp. 433-438. (Intervento presentato al convegno 14th IFAC Conference on Control Applications in Marine Systems, Robotics and Vehicles (CAMS 2022) tenutosi a Lyngby, Denmark nel 14-16 September 2022) [10.1016/j.ifacol.2022.10.466].
Energy-maximising model predictive control for a multi degree-of-freedom pendulum-based wave energy system
Papini, G.;Pasta, E.;Carapellese, F.;Bonfanti, M.
2022
Abstract
Renewable energy sources can be a solution for the recent pollution increasing scenario and the need for diversification of the energy market. Among such alternative sources,wave energy represents a viable solution, due to the its high power density and accessibility.Nonetheless, wave energy is still in phase of development, and a key stepping stone towards commercialisation is strongly linked to the availability of optimal control strategies for maximum energy harvesting. With its ability to handle system constraints and optimise power absorption directly, model predictive control (MPC) has gained popularity within the WEC community as a potential solution for the corresponding energy-maximising problem. In this study, an MPC strategy is developed for real-time control of the so-called PeWEC energy harvesting system,providing also a solution for the wave excitation estimation and forecasting problem, inherently required by the MPC controller to achieve optimal performance. Improved computational requirements are obtained via definition of a reduced control-oriented model, describing the dynamics of the system in a compact form. The performance of the proposed strategy is illustrated via a comprehensive numerical appraisal.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2973493