Renewable energy sources have acquired great relevance in the world context due to the guidelines taken by global policies. Although they are thermoelectric, biomass power plants are considered renewable energy sources because they maintain the levels of carbon dioxide in the atmosphere. In addition, thermoelectric plants have more autonomy in generation than other renewable sources such as hydro, wind and solar, which depend on uncertainties such as water flow, wind speed and solar irradiation, respectively. This set of characteristics makes biomass an indispensable energy source for future system operation planning. However, this source has intermittent periods as it is usually linked to the sugarcane crop. There are few prediction and simulation studies of this energy source. Thus, the dissertation aims to implement the Markov chain model with Monte Carlo simulations.