This paper proposes a social network search (SNS) algorithm for optimizing energy management systems (EMS) in microgrids. The EMS focuses on economic aspects, specifically addressing economic load dispatch (ELD) in both grid-connected and isolated operational modes, with a specific emphasis on integrating renewable energy resources (RES). The effectiveness and efficiency of the proposed SNS algorithm are evidenced through simulations using a microgrid model with five distinct cases, each featuring varying combinations of distributed energy resources (DERs). To ensure a comprehensive evaluation, the particle swarm optimization (PSO) algorithm is also utilized. The results show that the proposed SNS algorithm is effective in determining optimal dispatch strategies for DERs in all operational modes, as well as optimizing power transactions with the main grid to reduce operational costs in grid-connected configurations. Moreover, the proposed SNS algorithm outperforms the PSO algorithm in all cases studied. Furthermore, the findings highlight the positive impact of RES on total generation costs, demonstrating how increasing RES integration, particularly solar and wind power, contributes to lower microgrid costs and reduced dependence on external grid power procurement, thereby enhancing overall microgrid performance efficiency.