Hydrothermal systems optimal operation includes a step of optimizing the resources that are valued system storable. This optimization is performed traditionally by a stochastic dynamic programming in which the objective function to minimize is the expected value of future cost of operation, also known as Bellman function. While in theory, minimize the expected value of future cost of operation is “objective” in practice there are many reasons why the actual operation includes additional precautions, sometimes actually taken by operators who are the ones which have responsibility for the consequences of the operation or sometimes made based on safety considerations were not introduced in the optimization of the operation. This work shows the implementation on the platform Simulation of Electric Power Systems of stochastic dynamic programming algorithm for specifying the objective function cost reduction future with a certain probability of exceedance. This work was performed as part of the draft platform enhancements SimSEE with funding from the Energy Sector ANII. The paper presents the results of the operation to minimize the expected value of future cost and minimizing the risk value of 5% of being exceeded. Both operations are compared both costs achieved as in the qualitative aspects. The results allow evaluating the cost of being introduced by risk averse and also identify situations where there are major differences. It also discusses the impact on the marginal cost of system operation with a slogan risk averse. This value is relevant because it is the basis for calculating the Uruguayan market spot price. These scenarios correspond to the operation in 2017 with high penetration of wind energy in the system.