Optimal Scheduling of Distributed Energy Resources in Microgrid Using an Improved Equilibrium Optimizer

As the adoption of microgrids increases, optimizing their operation to improve energy efficiency and reliability remains challenging, especially given the unpredictable nature of renewable energy sources and varying load demands. This study aims to develop an improved equilibrium optimizer (IEO) for the optimal scheduling of a microgrid integrated with various distributed energy resources (DERs) and battery energy storage systems (BESS), aiming to reduce total generation cost. The IEO incorporates simple quadratic interpolation to improve the search capabilities of the original equilibrium optimizer (EO). This research examines three scenarios involving a typical grid-connected microgrid over a 24-hour period. The results demonstrate that generation costs are significantly lower in the case of active grid participation. Furthermore, the IEO method outperforms other approaches across all scenarios, evidencing its superior efficacy in identifying the cost-effective generation strategy for the microgrid.