This paper presents an Energy Management System (EMS) for a Multi-Microgrid (MMG) system that considers power exchanges between a set of interconnected microgrids (MGs) in an Active Distribution Network (ADN), taking into account electricity demand and renewable energy generation uncertainties using an Affine Arithmetic (AA) approach. The deterministic EMS model is formulated as a cost minimization problem which includes detailed operational constraints of thermal generators and Energy Storage Systems (ESSs) within each MG, as well as power flow limits at the Point of Common Coupling (PCC), considering all power exchanges among the set of MGs and the ADN. The uncertainties are formulated in the AA domain to obtain an EMS model that is robust for a range of realizations of the uncertain parameters, with no need of statistical assumptions or repeated calculations, which can be solved with relatively low computational burden, as opposed to other approaches such as Monte Carlo Simulation (MCS). The proposed AA model is then tested and validated with data of a set of MGs in an ADN located in Sao Paulo, Brazil, through comparisons with the deterministic model, MCS, and a Two-Stage Stochastic Programming (TSSP) approach. Results show an execution time improvement in the AA model of approximately 70% when compared to a MCS approach, which is expected to be slower, while considering the same range of uncertainties. Furthermore, the operation cost of the overall system decreases, as expected, by approximately 63% when power exchanges are enabled, as opposed to the individual operation of each MG, demonstrating the economic benefit of MMG systems.