A distinctive Dung Beetle Optimized (DBO) – Neuro Synergetic Aquila Controller (NSAC) for Grid-PV systems

• The Dung Beetle Optimized (DBO)-MPPT algorithm enhances power tracking efficiency, reducing tracking time to 0.4 s and recovery time to 0 .1s. • A high voltage gain converter minimizes switching loss and stress, boosting PV output voltage and overall system efficiency. • The Neuro-Synergetic Aquila Controller (NSAC) manages converter operation, optimizing power quality with LCL filters and reducing harmonics to 1.17 % THD. • Simulation results confirm the DBO NSAC model's effectiveness, achieving 99 % efficiency and surpassing conventional control techniques in performance. In the current energy landscape, solar photovoltaic (PV) systems that use Maximum Power Point Tracking (MPPT) controllers to produce the maximum amount of electricity have attracted a lot of interest. The bulk of standard MPPT approaches are shown to have issues with poor tracking efficiency, oscillations near MPP, and excessive time consumption, according to an analysis of the literature. A unique Dung Beetle Optimized (DBO) - MPPT regulating algorithm is to be designed as part of the proposed inquiry with the goal of increasing the total amount of electrical energy produced by PV panels under changing climate circumstances. Subsequently, a design for a high voltage gain converter is implemented to increase the output voltage of PVs while decreasing switching loss and stress. Subsequently, a Neuro-Synergetic Aquila Controller (NSAC) with an equivalent conversion rate is created to operate the converter. LCL filtering circuits and a three-phase voltage source inverter are used to optimize power quality while lowering harmonic levels. Furthermore, an extensive simulation research has been used to independently verify and evaluate the proposed DBO NSAC model with respect to IV-PV characteristics, efficiency, time, and other aspects. A comparison with some of the most up-to-date controlling techniques used in the ongoing investigations is also used to assess the overall efficacy and performance of the proposed model. The output findings show that the efficiency has reached 99 % with reduced THD of 1.17 %, which is a major improvement over the controlling approaches that are currently in use. By using the proposed DBO-MPPT model, recovery time is reduced to 0.1 s and overall power tracking time is decreased to 0 .4s.