Ensuring robust power tracking in microgrids: A new hybrid MPPT approach for improved dynamic behavior

Efficient energy extraction in photovoltaic (PV)-grid connected microgrids demands robust MPPT algorithms capable of maintaining maximum power output amidst sudden solar irradiance fluctuations and rapid load switching. This paper presents a comparative study of various MPPT techniques, including Perturb and Observe (P&O), Grey Wolf Optimization (GWO), Particle Swarm Optimization-tuned Adaptive Neuro-Fuzzy Inference System (PSO-ANFIS), hybrid Marine Predator Algorithm-Particle Swarm Optimization (MPA-PSO), Influential Flower Pollination Algorithm (IFPA), and a novel hybrid approach combining Artificial Ecosystem Optimization and P&O (AEO + P&O). To enhance tracking speed and system stability, the proposed AEO + P&O algorithm leverages the global search ability of AEO and the fast response of P&O. Results from dynamic microgrid operations reveal that AEO + P&O excels in performance, with a startup power output of 317.5 kW, settling at 670 kW during sudden irradiance fluctuations and returning to 487.3 kW after load changes. Under partial shading conditions, AEO + P&O outperforms other algorithms by maintaining the highest power output across varying irradiance levels, demonstrating superior convergence speed, stability, and robustness. Under full irradiance (1000 m²/s), AEO + P&O achieves 10.1 × 10⁵ W at the Point of Common Coupling (PCC), while under shaded conditions (Panel 1 at 800 m²/s and Panel 2 at 500 m²/s), it maintains 8.6 × 10⁵ W, outperforming other algorithms that show significant power drops. The proposed algorithm exhibits the lowest rise time (0.24 sec) and the minimum settling time (0.32 sec) compared to other MPPT techniques, offering faster tracking and higher accuracy. These results underscore two key objectives of the AEO + P&O algorithm: minimizing oscillations and convergence time while optimizing power extraction. As such, the proposed control solution is validated as a high-performance MPPT technique for the stable and reliable operation of PV systems within dynamic microgrids.