Microgrid Management of Hybrid Energy Sources Using a Hybrid Optimization Algorithm

Abstract

The microgrid of the renewable energy sources are used as photovoltaic (PV) panels, wind turbines (WT), fuel cells (FC), micro turbines (MT), diesel generators (DG), and battery energy storage systems (ESS), offers a promising solution. The issues posed by microgrid operators (MGOs) in managing energy from multiple sources, device as a storage, and response demand programs are addressed in this research study, which proposes a finest dispatch of energy approach for connected grid and microgrid freestanding. In order to accomplish successful energy management, the suggested strategy takes into account not only the minimization of operational expenses but also the reduction of power losses and greenhouse gas emissions. For microgrid energy management (MGEM), a new multi-objective solution integrating a demand response program is incorporated into a mixed-integer linear programming model. The optimization issue illustrates the techno-commercial benefits and assesses the effect of demand response on optimal energy dispatch. Furthermore, a hybrid optimization technique combining the African Vultures Optimization technique (AVOA) and Artificial Rabbits Optimization (ARO) is projected to holder the problem of optimization, and an optimized fuzzy interface is built for scheduling the ESS. Finding the best trade-offs between costs, emissions, and power losses is made possible by the algorithm, which offers insightful information for the microgrid energy management system. The outcome of the renewable energy sources of the all categories are examined.