Microgrid Energy Management System Using Adaptive Bat Optimization Technique

The escalating demand for efficient and sustainable energy solutions has led to the prominence of micro grids, localized energy systems that integrate renewable sources and enhance energy resilience. Microgrids often incorporate diverse energy sources like solar, wind, and batteries. Effective energy management ensures these sources are utilized efficiently to meet the energy demands of the local community or facility. Efficient energy management in microgrids promotes the use of renewable energy sources, reducing reliance on fossil fuels and lowering greenhouse gas emissions, thus contributing to environmental sustainability. This paper introduces a novel approach for optimizing the operation of micro grids through the utilization of an Adaptive Bat Optimization (ABO) technique. The proposed Microgrid Energy Management System (MEMS) aims to maximize the utilization of renewable energy sources, minimize operational costs, and ensure grid reliability. The Adaptive Bat Optimization technique, inspired by the echolocation behavior of bats, is employed to dynamically adjust the control parameters of the Microgrid components, including distributed energy resources, energy storage systems, and demand-side loads. Simulation results demonstrate that the proposed microgrid energy management system minimized the total generation cost up to 487.5 ∃ per day, and it shows the effectiveness of the proposed approach in achieving optimal Microgrid operation, as evidenced by improved economic performance, a reduced carbon footprint, and enhanced system stability.