Optimized Control and Integration of Renewable Energy Sources in ADN Using High Gain SEPIC Converter and Adaptive Grasshopper-PI Controller

Resumo

In recent years, incorporating renewable energy into Active Distribution Networks (ADNs) significantly reduces greenhouse gas emissions by replacing fossil fuel-based generation with clean energy sources. Hence, this study explores an ADN configuration featuring a Photovoltaic (PV) system and a Doubly-Fed Induction Generator (DFIG)-based wind energy conversion system (WECS). A high gain improved Single-Ended Primary Inductor Converter (SEPIC) is utilized to boost the PV voltage into required level for ADN. The SEPIC converter's operation is precisely regulated by an Adaptive Grasshopper Optimization Algorithm (AGOA) tuned Proportional-Integral (PI) controller, ensuring optimal performance and efficiency. In parallel, the DFIG-based WECS is connected to a Pulse Width Modulation (PWM) rectifier, which is managed by a PI controller. To enhance the system's resilience and stability, a bidirectional converter is integrated with a battery storage system, allows for efficient energy management in which excess energy generated by the RES during peak production periods is stored in the battery. The performance of the developed system is validated through MATLAB/Simulink and the outcomes establishes that the developed converter together with control approach outperform in higher efficiency of 95% with minimal settling time and convergence speed.