An improvement of Global Maximum Power Point Tracking Using a Novel Grasshopper Optimisation Algorithm of Photovoltaic System

The performance of solar photovoltaic (PV) panels is entirely determined by ambient temperature, solar irradiance, and dynamic environmental conditions. As a result, the photovoltaic system exhibits multiple peaks in the I-V and P-V curves during partial shading conditions (PSC), which significantly reduces power output. The maximum power point tracking (MPPT) method is essential for extracting maximum power from the PV panel during PSC. With conformist MPPT algorithms, determining the maximum power point is unrealistic. To overcome the constraints, this paper proposes the grasshopper optimisation algorithm (GOA), which imitates the behaviour of grasshopper swarms in nature and is capable of extracting maximum power even during unfavourable shading conditions. The performance assessment of GOA method has been carried out in the MATLAB/SIMULINK environment. This algorithm effectiveness is validated by comparing its performance with conventional and other most prominent global search counterparts. The proposed algorithm is validated in real-time hardware with boost converter through different PV array pattern. The outcome demonstrates the effectiveness of the proposed algorithm which drastically reduces the computation time and performs rapidly and precisely to extract the global maximum peak with minimal oscillations.