Multi-objective hybrid GA-PSO optimized PI control for grid-connected PV-fed cascaded H-bridge multilevel inverter

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Power Electronics

Background:

• Grid integration of photovoltaic (PV) energy systems requires sophisticated control for stability and power quality.
• Cascaded H-bridge multilevel inverters (CHB-MLI) are crucial for grid-connected PV applications.

Purpose of the Study:

• To develop and validate a closed-loop control strategy for a PV-integrated on-grid five-level CHB-MLI.
• To enhance dynamic response and improve power quality in grid-connected PV systems.

Main Methods:

• Utilizing a hybrid Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) technique for optimal tuning of Proportional-Integral (PI) controllers.
• Implementing a multi-objective fitness function to minimize Total Harmonic Distortion (THD), DC-link voltage imbalance, steady-state error, and settling time.

Main Results:

• Simulation results using MATLAB/Simulink demonstrate the controller's feasibility.
• Real-time validation on an OPAL-RT simulator confirms the robustness and practical effectiveness of the proposed control method.

Conclusions:

• The hybrid GA-PSO-based PI control effectively enhances dynamic performance and power quality for grid-connected PV systems using CHB-MLI.
• The proposed control strategy is robust and suitable for practical implementation in modern power grids.