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This paper presents a model for the simulation of the optimal medium-term operation of a hydrothermal system. System stochastic parameters are modeled by Monte Carlo scenarios, which are solved on distributed processors. For each scenario a yearly hydro-thermal scheduling (HTS) problem with hourly time resolution is formulated and solved as a large mixed integer linear program (MILP). HTS modeling includes unit commitment, start-up costs and minimum up/down time constraints. The model is applied to the Greek power system, comprising 29 thermal units and 13 hydroplants; 100 simulation scenarios are generated and solved on 18 distributed processors. Test results include both medium-term objectives, such as reservoir water management, and short-term decisions such thermal unit start-up decisions.