Effectiveness of a GNG-based MPPT and related control system for marine current turbines in unsteady operating conditions

This paper presents the validation of a MPPT technique, based on a Growing Neural Gas (GNG) network, for high performance marine current generator with induction machine, in presence of torque oscillations caused by time and space variation of the turbine operating conditions. The unsteady torque delivered by a notional turbine working in the presence of waves and of sea bottom boundary layer is obtained by an unsteady hydrodynamic formulation based on a Boundary Element Method (BEM). The performance of MPPT has been experimentally tested on test bench equipped by a turbime emulator, an induction generator and a back-to-back power converter configuration with two voltage source converters, one on the machine side and the other on the grid side controlled with a high performance vector control technique, respectively Field Oriented Control (FOC) and Voltage Oriented Control (VOC). Experimental results show the correct behaviour of the proposed MPPT technique which permits to instantaneously estimate the sea speed and correspondingly to compute the optimal machine reference speed for tracking the maximum available power even in presence of the sea waves.

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