The increasing amount of Renewable Energy Sources (RES) results in an increasing uncertainty in electricity generation, which has to be taken into account in energy market simulation models. This work, which is a collaboration between R.S.E. S.p.A (former Cesi Ricerca S.p.A.) and the University of Bergamo, deals with the implementation of Stochastic Programming techniques [5] into the MTSIM electricity market simulator in order to take into account wind generation uncertainty. Originally developed by R.S.E, MTSIM [1] is a medium term (time horizon spanning from some weeks to one year) zonal electricity market simulator, which calculates the optimal (in terms of minimization of generation costs) hourly Unit Commitment and Dispatching of thermal and hydro generation plants; moreover, it can also optimize the development of inter-zonal transmission capacity. MTSIM is used in scenario analyses for a wide range of applications: from the feasibility study of a single generation plant to the development of the cross-border European Transmission Network [2][3][4]. The newly introduced stochastic approach models the day-ahead electricity market, where energy bids submitted for the day ahead are based on wind generation forecasts which will necessarily di_er from the actual wind generation. From the hourly data of forecasted and actual wind generation (available on the web site of the Italian TSO TERNA) a statistical distribution of the forecasting error can be built. Then, by considering this error distribution around a mean wind generation pro_le, wind generation scenarios are created. Future developments of this work will be aimed to make MTSIM able to take into account uncertainty related to other kinds of RES intermittent generation as well as to demand.