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A new model for long-term operation of hydrothermal power systems is introduced and a method for obtaining an optimal solution is also developed. The authors assume that reservoir inflows and energy demand are stochastic and all units are exposed to random outages. The objective is to minimize the total cost of the system as well as the expected interruption cost of energy (EIC) during a given planning horizon. This goal is reached through determination of hydroplant discharges, thermal units energy output, and the system reliability level simultaneously. In fact, the authors integrate long-term hydrothermal system operation planning and system reliability determination in a unified model. Since the resulting model is a large-scale stochastic nonlinear programming, an algorithm is especially developed to solve it. This algorithm that includes decomposition technique, Lagrangian relaxation, and nonlinear and dynamic programming finds an optimal solution within three stages. To test the method, it is implemented for the Khuzestan power system in Iran and the results are analyzed.