KEYWORD |

#### Data-based modelling of nonlinear hydrodynamics for wave energy conversion systems

keywords CONTROL SYSTEMS, DATA ANALYSIS, MODELLING, SYSTEM DYNAMICS, SYSTEM IDENTIFICATION, WAVE ENERGY - HYDRODYNAMICS - NUMERICAL MODELLING

Reference persons NICOLAS EZEQUIEL FAEDO, GIUSEPPE GIORGI

Research Groups MORE Lab _ http://www.morenergylab.polito.it

Thesis type MASTER THESIS

Description Wave energy conversion devices, commonly referred to as wave energy converters (WECs), need to be

controlled in order to maximise the energy extraction from the ocean wave resource, hence directly

lowering the associated levelised cost of energy.

Control for WEC systems departs from standard regulation/tracking objectives, commonly employed in

control engineering: The objective is that of maximising energy extraction, and not that of

following/tracking a given set-point/reference. As such, the vast majority of the WEC control techniques

employ lie within the field of optimal control theory, where an associated optimal control problem

(OCP) is solved in real-time to compute the corresponding control action.

OCPs are virtually always model-based: That is, a dynamical model of the WEC system is required in

order to predict future motion, enforce constraints, and maximise the energy objective. These models

need to be parsimonious in terms of both computational and analytical complexity, in order to facilitate

real-time calculations, i.e. to be implementable.

Nonetheless, being the Navier-Stokes equations the starting point for WEC modelling, computing

control-oriented models can be a daunting task. As a matter of fact, recently, a particular class of wave-induced nonlinear effects has been deemed to be particularly relevant for controlled devices.

This project will explore the use of data-based modelling for to compute parsimonious dynamical representations of WEC systems, based on mid-fidelity solvers. The resulting models will be used both for analysis and optimal control purposes.

See also main.pdf

Required skills Linear algebra, fundamentals of physical modelling, transfer functions, state-space systems.

Deadline 28/08/2024
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