The decentralisation of power generation introduces new reliability challenges to the grid mainly due to the intermittent nature of renewable resources. From the grid perspective, the reliability issues, caused by generation-demand imbalance, can be mitigated by Energy Storage Systems (ESS) participating in the electricity arbitrage market. From the customer perspective, participating in the energy market can potentially improve the economic viability of Microgrids (MG). In this context, establishing a detailed model, reflecting the limitations and operating behaviour of components within the MG is essential. Furthermore, tracking the fluctuations in renewable generation, energy demand, and dynamic pricing are of paramount concern in cost-effectively controlling the power flow in MGs. In the light of the above, this paper proposes a model predictive-based energy management system in presence of dynamic pricing, aiming at minimising the operating cost and lessening the impact of uncertainty on the day-ahead basis prediction while meeting the demand requirement. The presented results prove the functionality and applicability of the proposed framework for mid-scale commercial MGs at the distribution level.