This paper proposes a new adaptive neural control (ANC) based strategy for maximum power point tracking (MPPT) in a photovoltaic (PV) system. The proposed strategy exploits the online trained adaptive linear neuron (ADALINE) technique. This results in a simple, fast and accurate MPPT algorithm which is easy for implementation. The ANC method is based on the incremental conductance and implemented in direct control mode. Tracking performances of the proposal are experimentally assessed using the EN 50530 standard dynamic tests. A comparison with perturb and observe algorithm is achieved. Superiority of the suggested method in terms of tracking features, convergence speed and oscillatory behaviors reduction is proven. The originality of this work is the design of an efficient and simple ADALINE based MPPT algorithm that reaches very quickly the maximum power point. Moreover, the proposal is experimentally tested in a real PV system according to the EN 50530 standard.

Keywords: Adaptive neural control, Maximum power point tracking, Perturb and observe algorithm, Photovoltaic system