Marine current turbine generator system with induction machine growing neural gas (GNG) MPPT based on sensorless sea speed estimation

This paper presents a MPPT technique for high performance marine current generator with induction machine based on the Growing Neural Gas (GNG) network. The marine turbine characteristic curve has been firstly predicted by a BEM hydrodynamic formulation. The BEM analysis has been compared with experimental results obtained at the QinetiQ cavitation tunnel (Haslar Marine Technology Park). For the experimental application, a back-to-back power converter configuration with two voltage source converters has been considered, one on the machine side and the other on the grid side. Each converter has been controlled with a high performance vector control technique, respectively Field Oriented Control (FOC) and Voltage Oriented Control (VOC). A test setup has been built for the experimental assessment of the methodology. 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.