Abstract
The work shows a mathematical model that aims to perform an estimation by statistical methods of electrical energy consumption. It consists of an algorithm, simulates the power consumption of the main electrical loads of the building. For its execution it is required to have initial parameters. These parameters were collected and analyzed using Monte Carlo methods and the assignment of distribution probabilities to predict their use, the calculation of the general consumption of the building was performed. Based on the diagnosis made, the model is validated with real data on the building’s power and energy consumption from consumption bills. In this way, a case study is carried out to identify weaknesses and possible improvements to the building’s energy management. The result of the application of the mathematical model is a set of estimated daily demand curves and their data matrices, which are used to calculate the stochastic energy consumed by the building per day and per month. This analysis is compared with the real values of the consumption measurements and invoicing, in order to show an improved electrical load profile that will result in savings in the payment of electrical energy and improvement in energy use habits.
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