Novel integration of 50 kW photovoltaic systems in microgrids using quantum slime mould optimization for enhanced power output and efficiency

This paper presents the integration of a 50 kW grid-connected photovoltaic (PV) system with a quantum slime mold optimization (QSMO)-based maximum power point tracking (MPPT) algorithm to enhance power extraction, tracking stability and grid integration under varying irradiance conditions. A high-gain DC–DC converter is incorporated to improve voltage boosting capability and overall conversion efficiency. The proposed system is modelled and validated in MATLAB/Simulink under partial shading and dynamic environmental conditions. Simulation results demonstrate that the proposed QSMO algorithm achieves a maximum MPPT efficiency of 99.96%, outperforming the conventional Adaptive Slime Mould Optimization (ASMO) (95.87%) and Adaptive Particle Swarm Optimization (APSO) (90.82%) approaches. Furthermore, the proposed QSMO method maintains low THD values of 1.2%, 1.7%, 2.2% and 2.4% at irradiance levels of 1000, 850, 650 and 450 W/m2, respectively, indicating improved power quality and grid compliance. The proposed high-gain DC–DC converter delivers an output of approximately 460 V and 75 A, compared with 450 V and 60 A obtained using the conventional boost converter, resulting in enhanced power transfer capability and reduced conversion losses. Qualitative analysis further confirms that the QSMO algorithm provides faster convergence, superior tracking accuracy, lower output ripple, improved voltage and current stability and robust operation under partial shading conditions.