The main part of the code.

The growing concerns over fossil fuel dependency, environmental impacts, and escalating energy expenses highlight the critical importance of enhancing energy system efficiency. This study presents a dual-phase optimization approach for improving grid-connected microgrid (μG) operations, focusing on Sodium-Sulfur (NaS) and Sodium Nickel Chloride (Na-NiCl₂) battery storage systems. The problem was structured as a mixed-integer nonlinear programming (MINLP) model and resolved using GAMS software with its embedded open-source BONMIN solver. The initial phase establishes optimal battery storage system (BSS) allocation methods to optimize renewable energy source (RES) self-consumption (SC), increase hosting capacity (HC), and minimize operational expenses. Building on these results, the second phase develops optimal microgrid operational strategies to reduce total operating costs further. The research evaluates five scenarios with incrementally increasing the number of BSSs, ranging from one to five units. Through this systematic analysis, the work demonstrates that both the quantity and type of BSS units significantly impact μG operating costs. The most efficient configuration emerged in Case 3, where three Na-NiCl₂ BSS units achieved a 32.35% reduction in operating costs. Additionally, the integration of BSS demonstrated notable improvements in both HC and SC rates.