Enhancing grid connected photovoltaic systems performance using a bio-inspired MFB algorithm for efficient maximum power point tracking

An original bio-inspired approach, modeled after the magnificent frigatebird, is proposed in this study to optimize Maximum Power Point Tracking (MPPT) for photovoltaic arrays operating in grid-tied configurations, in response to the growing demand for higher efficiency during the ongoing transition toward sustainable energy. By modeling the frigatebird’s strategic shifts between wide-range scouting and target-focused behavior, the algorithm maintains a dynamic equilibrium between exploration and exploitation, ensuring robust MPPT performance even under rapidly changing irradiance and temperature conditions. The photovoltaic setup under study consists of a 50 kW SunPower panel array, paired with a boost-type DC–DC converter and a three-phase inverter. System behavior was examined in MATLAB/Simulink across three operating scenarios: standard test benchmarks, fast-changing irradiance conditions, and real-world solar measurements collected in Tetouan, Morocco. Simulation outcomes reveal that the MFB-based control achieves a high energy conversion efficiency of 99.5% with a rapid response time of 0.27 s, providing improved performance compared with widely used MPPT methods such as P&O and ABC in terms of dynamic response, tracking precision, and total harmonic distortion (THD). The proposed algorithm relies on a simple computational structure with a limited number of control parameters, contributing to reduced computational burden and supporting its suitability for real-time embedded MPPT applications. A performance comparison against fourteen other MPPT approaches reported in recent studies further supports the effectiveness and adaptability of the proposed method. The findings indicate that MFB represents a promising and scalable solution for advanced smart PV systems, with potential applications in real-time embedded platforms and hybrid renewable energy networks. While the present validation is based on detailed simulation results, experimental implementation and hardware-based assessment are considered as natural extensions of this work.