Towards Sustainable Energy Management: Enhancing PV Performance in DC Microgrids with the Aquila Approach

The emergence of DC microgrids has heightened interest in optimizing photovoltaic (PV) panels and storage systems to enhance energy management, minimize power losses, and bolster system stability.This study addresses a critical gap in current methodologies by proposing the Aquila algorithm, an optimization technique specifically designed for the unique characteristics of DC power distribution systems.Unlike traditional optimization methods that primarily cater to AC microgrids, the Aquila algorithm uniquely focuses on the intricate dynamics of DC microgrids, enabling it to determine optimal locations and sizes for PV panels and battery storage systems effectively.The efficiency of the proposed PV system optimization was validated using a MATLAB/Simulink model, with simulations executed under controlled settings to ensure accurate results.Notably, the system achieved a rapid settling time of just 0.2 seconds during load fluctuations, with the Aquila algorithm mitigating temporary imbalances and deviations in key parameters like grid power, battery power, and load power.Simulation results revealed that the PV system operated under a solar irradiance level of 700 W/m, generating a controlled power output of 10 kW with a corresponding PV output of 8 kW.The algorithm demonstrated a significant reduction in system oscillations and fluctuations, ensuring consistent performance even when sudden load changes occurred.At a critical moment (t = 0.025 s), the Aquila algorithm-maintained system stability despite a drop in solar generation, thus emphasizing its reliability in adapting to varying solar conditions.Overall, the findings indicate that the Aquila algorithm significantly enhances energy management within PV-connected DC microgrids, optimizing battery performance and improving overall system reliability and efficiency.This research presents a promising approach for optimizing battery-connected PV systems, ultimately contributing to the advancement of sustainable energy solutions within DC microgrid frameworks.