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SWELL - Smart Wave Energy Conversion via Learning and Low-Cost Control (SWELL)

Duration:
16/06/2026 - 15/06/2029
Principal investigator(s):
Project type:
UE-funded research - HE - Excellent Science - MSCA
Funding body:
COMMISSIONE EUROPEA
Project identification number:
101276493
PoliTo role:
Coordinator

Abstract

This project (SWELL) aims to pioneer the next generation of smart control technology for wave energy converters (WECs), addressing the urgent challenge of reducing their levelized cost of energy to attract investments in this promising renewable energy technology. Despite recent progress in WEC control, improvements in wave energy conversion remain limited due to the difficulties of handling accurate nonlinear models in the controller design. To overcome this, SWELL will develop the first data-driven model predictive controller (MPC) tailored to WECs, combining cutting-edge control methods, hydrodynamics, and machine learning. SWELL will deliver accurate and validated models capturing the ubiquitous nonlinear effects of WECs and exploit them in the design of an MPC that optimizes energy conversion.

By integrating expertise from three world-class hosts, the unique nature of SWELL will enable efficient, fast, and practical control implementation with real-time capabilities and a low-cost design, supporting the pathway towards the effective commercialization of wave energy. This project comprises four scientific work packages, which accomplish: (i) accurate nonlinear hydrodynamic modeling of wave energy converters, (ii) efficient MPC design exploitating the explicit MPC paradigm enabled by convex relaxation techniques, (iii) experimental validation of the developed models and control, through the definition of a custom analog electronic circuit efficiently implementing the designed MPC, and (iv) release of open-source software implementing the developed methods. This fellowship will expand the career horizons of the fellow through a highly multidisciplinary plan, building upon and extending beyond his current competencies. The fellow is well-positioned to undertake this project, enabling him to develop innovative concepts based on his PhD research. The unprecedented nature of this action will launch the fellow on a trajectory to a productive scientific career.

People involved

Structures

Partners

  • POLITECNICO DI TORINO - AMMINISTRAZIONE CENTRALE - Coordinator
  • The University of Western Australia

Keywords

ERC sectors

PE1_19 - Control theory and optimisation
PE6_7 - Artificial intelligence, intelligent systems, multi agent systems
PE7_1 - Control engineering
PE8_3 - Civil engineering, architecture, maritime/hydraulic engineering, geotechnics, waste treatment
PE8_6 - Energy processes engineering

Sustainable Development Goals

Obiettivo 7. Assicurare a tutti l’accesso a sistemi di energia economici, affidabili, sostenibili e moderni|Obiettivo 13. Promuovere azioni, a tutti i livelli, per combattere il cambiamento climatico*

Budget

Total cost: € 332,913.72
Total contribution: € 332,913.72
PoliTo total cost: € 332,913.72
PoliTo contribution: € 332,913.72