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This paper presents a stochastic model for self-scheduling of a thermal power producer which participates in day ahead joint (simultaneous and aggregated) energy and reserves markets. The paper analyzes a scenario-based approach that considers random distribution, such as force outages of generating units as well as price forecasting inaccuracies. The above uncertainties are modeled as scenario tree using a combined Fuzzy C-Mean/Monte-Carlo Simulation (FCM/MCS) method. With the above procedure the stochastic optimization problem is converted into corresponding deterministic problem which is formulated as a mixed integer nonlinear programming (MINLP) problem. Numerical simulations for a power producer with 21 generating units are discussed to demonstrate the effect of price uncertainties and unit's forced outages on the scheduling of units.