This paper presents a study on a Solar-Wind hybrid system that is connected to the electrical grid in a three-phase power grid configuration. The system integrates a PV station and a wind farm at the Point of Common Coupling (PCC) to improve its performance. The Maximum Power Point Tracking (MPPT) technique is used to obtain maximum power output under different weather conditions for both the PV and wind energy conversion systems. An Artificial Neural Network (ANN) controller is developed to track the maximum power point of the PV array and is evaluated under various weather conditions. The Vector Control technique is used to control the three-phase neutral point clamped multilevel inverter with the ANN controller to regulate the DC-link voltage to the desired level. The simulation of hybrid system is conducted using MATLAB/SIMULINK and compare the performance of the ANN controller with a PI controller in terms of the step responsiveness of the DC-link voltage and the efficiency of the MPPT technique. The results indicate that the ANN controller efficiently maintains a constant grid voltage, provides unity power factor, and optimally utilizes the injected active power from the Solar-Wind hybrid power system, regardless of the fluctuations in environmental conditions. Overall, the paper proposes a comprehensive approach for developing a Solar-Wind hybrid system that enhances its performance and optimizes power output under various weather conditions, using the MPPT technique and ANN controller for effective control of the DC-link voltage.