Inserting renewable energy in the electric grid in a decentralized manner is a key challenge of the energy transition. However, at local stage, both production and demand display erratic behavior, be it for the dependence upon local weather conditions. Thus, the match between supply and demand is delicate to achieve in such a stochastic context. It is the goal of Energy Management Systems (EMS) to achieve such balance at least cost. We present EMSx, a numerical benchmark for testing control algorithms for the management of electric microgrids doted with a photovoltaic unit and an energy storage system. Our benchmark is based on a rich collection of historical observations and forecasts collected by the company Schneider Electric. Besides the dataset, we also publicly release \emsx, a package implemented in the Julia language which enables to easily implement a microgrid controller and to test it on the EMSx benchmark. Eventually, we showcase the results of standard microgrid control methods, including Model Predictive Control, Open Loop Feedback Control and Stochastic Dynamic Programming.