Coati Optimization Algorithm for Enhanced Energy Management in AC/DC Hybrid Microgrids

Abstract

The Coati Optimization Algorithm is introduced as a novel approach for optimizing energy management in AC/DC hybrid microgrids, addressing the increasing complexities of integrating renewable energy sources and electric vehicles. This research highlights the algorithm's capability to enhance optimal power flow by efficiently managing renewable energy uncertainties, thus ensuring stability and reliability within microgrid operation. Extensive simulations demonstrate that the enhanced coati optimization not only outperforms traditional methods in achieving energy efficiency but also reduces operational costs. The algorithm's nature-inspired mechanism allows for rapid convergence and improved solution accuracy, showcasing its adaptability to varying energy demand scenarios. This study contributes to advancing the field of smart grid technology, positioning the Coati Optimization Algorithm as a significant tool for facilitating sustainable energy management practices in future microgrid applications. Through comprehensive analysis and validation, the methodology paves the way for more resilient and efficient energy systems.