MPPT efficiency enhancement of a grid connected solar PV system using Finite Control set model predictive controller

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Photovoltaic (PV) systems require Maximum Power Point Tracking (MPPT) to optimize energy harvesting.
• Existing MPPT strategies face challenges in efficiency and dynamic response.
• Grid-connected PV systems need advanced control for stable and efficient power delivery.

Purpose of the Study:

• To develop and evaluate a Model Predictive Control (MPC) strategy for MPPT in a 20 kW grid-connected PV system.
• To enhance the AC load energy tracking efficiency of PV systems.
• To compare the performance of the proposed MPPT strategy against conventional methods like Perturb and Observe (P&O).

Main Methods:

• A PV system model was developed in MATLAB/Simulink, incorporating a DC-DC boost converter and a three-phase, two-level voltage source inverter (VSI).
• Finite Control Set Model Predictive Control (FCS-MPCC) was implemented for the VSI, utilizing Space Vector Pulse Width Modulation (SVPWM).
• An inner-loop current controller with dq-coordinate transformation and a Phase-Locked Loop (PLL) for grid synchronization, along with an RL filter for harmonic reduction, were employed.

Main Results:

• The FCS-MPCC strategy achieved a power tracking efficiency of 99.80%.
• This performance significantly surpasses the conventional Perturb and Observe (P&O) method, which yielded 97.72% efficiency.
• The proposed controller demonstrated a faster time response and reduced oscillations around the maximum power point.

Conclusions:

• The proposed FCS-MPCC strategy offers a superior approach for MPPT in grid-connected PV systems.
• This advanced control method enhances energy harvesting efficiency and system stability.
• The results indicate a significant improvement over existing MPPT techniques, paving the way for more efficient solar energy utilization.