Optimizing control and management of hybrid power system, consisting PV-wind and battery-super capacitor, using COOT...

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Grid integration of renewable energy sources like solar PV and wind turbines introduces challenges, notably harmonic distortion.
• Existing control strategies often struggle to balance maximum power extraction with grid stability.

Purpose of the Study:

• To develop and evaluate an advanced control strategy for a grid-connected hybrid power system.
• To maximize energy harvested from PV arrays and wind turbines while minimizing Total Harmonic Distortion (THD) injected into the grid.

Main Methods:

• Implementation of a hybrid storage system (batteries and supercapacitor).
• Development of a cascade PI-PID controller optimized using the COOT bird algorithm for various control loops (MPPT, PMSG, BESS, Supercapacitor, GSC).
• Comparison with a Genetic Algorithm (GA)-tuned PI controller under realistic, dynamic operating conditions.

Main Results:

• The proposed PI-PID controller achieved significant reductions in voltage and current oscillations (30% and 81% respectively).
• The supercapacitor effectively mitigated peaks generated by the controller, enhancing system stability.
• The energy management strategy successfully maximized renewable energy utilization under variable conditions.

Conclusions:

• The COOT-optimized cascade PI-PID controller offers superior performance for hybrid renewable energy systems compared to traditional methods.
• Hybrid storage systems, particularly with supercapacitors, are crucial for managing intermittency and improving power quality.
• The proposed approach ensures efficient energy exploitation and grid stability in complex, real-world scenarios.