Adaptive power management strategies for arrays of oscillating water column wave energy converters.

The aim of this project is to develop a novel framework of optimal and adaptive control strategies for large arrays of oscillating water columns (OWC) that can guarantee maximum power on the one hand, and minimum power oscillation on the other. The framework will combine multi-objective optimisation with adaptive learning algorithms. First, we will analyse the response of OWC networks to different sea states and wave conditions. Second, we will build a combined individual (distributed) and central (supervisory) control architecture. Distributed optimal control strategies for the turbine and generator configurations will be integrated into a supervisory adaptive control network to address the two control objectives: (a) optimising power generation of individual OWCs while adaptively establishing a power phase shift regime for the OWC array to reduce overall power oscillation; (b) robust operation via adaptive learning algorithms to track modelling uncertainties and disturbances.