Renewable energies are revolutionizing the market and electrical networks. These changes present a challenge for all agents of the electrical system; in particular, for those who want to predict or plan the state of the electrical network in the future. In recent years, the intermittent nature of these energy sources has become a planning problem that many have tried to solve, proposing different methods. Since 2013, UTE, the national electricity company of Uruguay, has been implementing algorithms to solve the probabilistic load flow calculation based on the Monte Carlo method. In this work, the use of Point Estimation is proposed, an alternative method faster than Monte Carlo, although less precise, and which has a strong support in recent scientific publications. A real application of the Point Estimation algorithm to the Uruguayan network is presented and it is compared with the classic Monte Carlo Method. The results on the Uruguayan system are promising, showing that the method allows to capture the general performance of the system in a time at least one order less than Monte Carlo.