The share of steel production via the scrap-electric arc furnace route tends to increase worldwide, since steel can be recycled almost completely. In addition to the lower specific energy consumption and lower emissions, the scrap-electric arc furnace route is more environmentally friendly than other steel production routes. In order to be able to derive further optimization possibilities for this process route regarding energy efficiency and demand side management, load profiles of the consumers are required for the different operational load situations in order to be able to evaluate further optimization options for this process route. The aim of this master’s thesis is to develop an electric energy system model for the Breitenfeld Edelstahl steel mill. This model is aimed to offer the possibility of analyzing and evaluating potentials for demand side management and optimization options. For this purpose, process parameters and power are recorded for the respective electrical units in the steel mill. These real electrical load scenarios are analyzed, and synthetic load profiles are created for active, reactive and apparent power with a temporal resolution of one minute. For modeling the synthetic load profiles, a uniform concept is established and different stochastic as well as statistical methods are used. By combining the individual synthetic load profiles, the energy system model is obtained, which depicts the energy system of the steel mill. Finally, the synthetically generated load profiles for the respective units as well as the overall energy system are validated. For this purpose, the data generated from the simulation is compared with the measured data and the results are analyzed and evaluated regarding to their accuracy.