This paper proposes a new hybrid maximum power point tracking (MPPT) control strategy for grid-connected solar systems based on Incremental conductance—Particle Swarm Optimization and Model Predictive Controller (IncCond-PSO-MPC). The purpose of the suggested method is to create as much power as feasible from a PV system during environmental changes

then transfer it to the power grid. To accomplish this

a hybrid combination of incremental conductance (IncCond) and particle swarm optimization (PSO) is proposed to locate maximum power

followed by model predictive control (MPC) to track maximum power and control the boost converter to achieve high performance regardless of parameter variations. A two-level inverter

likewise

controlled by Model Predictive Control

is employed to inject the PV power generated. In this application

the MPC is based on minimizing the difference between the reference and prediction powers

which is computed to select the switching state of the inverter. The proposed system is simulated and evaluated in a variety of dynamic conditions using Matlab/Simulink. Results reveal that the proposed control mechanism is effective at tracking the maximum power point (MPP) with fewer power oscillations.