Optimal management of energy storage systems in grid-connected microgrid

The increasing variability of electrical loads and distributed renewable generation is driving the need for enhanced flexibility in distribution systems. Grid-connected microgrids equipped with battery energy storage systems (BESSs) represent a key solution to provide flexibility by actively controlling the power exchanged with the utility grid. This paper proposes an optimization-based energy management strategy aimed at maximizing operational flexibility while reducing peak demand and grid dependency. The proposed approach formulates the microgrid energy management problem as a mixed-integer linear programming (MILP) model, enabling accurate representation of battery operational constraints, discrete charging and discharging states, and predefined grid power exchange profiles. Two complementary operating modes are investigated. The first mode focuses on flexibility provision through peak demand reduction by enforcing stepped grid absorption profiles over a daily horizon. The second mode addresses flexibility from a planning perspective, determining the minimum storage investment required to achieve a fully flat grid power profile. By explicitly enforcing state-of-charge neutrality over the scheduling horizon, the proposed framework ensures repeatable daily operation and preserves battery lifetime. The effectiveness of the strategy is validated through a real-world case study based on a university microgrid with photovoltaic generation, demonstrating significant peak reduction and enhanced flexibility in grid interaction. The results highlight the role of energy storage as a flexibility-enabling asset and confirm the suitability of MILP-based approaches for realistic microgrid energy management applications.