Marine Predator Algorithm-Based Optimal PI Controllers for LVRT Capability Enhancement of Grid-Connected PV Systems

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Photovoltaic (PV) systems integration into power grids is increasing, necessitating robust grid stability measures.
• Low-voltage ride-through (LVRT) is critical for PV systems to maintain grid stability during voltage disturbances like sags.
• Proportional-Integral (PI) controllers are standard solutions for managing PV system responses, but their optimal tuning is challenging.

Purpose of the Study:

• To propose a novel Marine Predator Algorithm (MPA) for optimizing PI controller parameters in PV inverters.
• To enhance the low-voltage ride-through (LVRT) capability of PV systems through improved inverter control.
• To evaluate the effectiveness of MPA-tuned PI controllers in mitigating overshoot, undershoot, settling time, and steady-state errors.

Main Methods:

• Developed a unique algorithm using the Marine Predator Algorithm (MPA) to optimize the PI controller's fitness function.
• Focused on inverter control strategies to improve system performance during grid disturbances.
• Tested the proposed methodology under a 3-phase line-to-ground (3L-G) fault scenario.

Main Results:

• The MPA-optimized PI controller demonstrated superior performance compared to Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO).
• Achieved 14% to 40% reduction in overshoot for DC-Link Voltage and active power compared to PSO and GWO.
• MPA resulted in faster settling times, being 0.76 to 0.95 seconds quicker than PSO and GWO.

Conclusions:

• The Marine Predator Algorithm offers an effective approach for tuning PI controllers to enhance PV system LVRT.
• Optimized PI controllers significantly improve system response characteristics, including overshoot, undershoot, and settling time.
• The MPA-based method provides a promising solution for improving the stability and reliability of renewable energy integration.