In the new global and local scenario, the advent of intelligent distribution networks or Smart Grids allows real-time collection of data on the operating status of the electricity grid. Based on this availability of data, it is feasible and convenient to predict consumption in the short term, from a few hours to a week. The hypothesis of the study is that the method used to present time variables to a prediction system of electricity consumption affects the results.

Traditional forecasting models have been widely used for decision-making in production, finance and energy. Such is the case of the ARIMA models, developed in the 1970s by George Box and Gwilym Jenkins [1], which incorporate characteristics of the past models of the same series, according to their autocorrelation. This work compares advanced statistical methods for determining the demand for electricity in Colombia, including the SARIMA, econometric and Bayesian methods.

he professional practices represent a space for interorganizational and intersectoral alliances that contribute to the development of localities and regions. From this referent, the design and validation of intersectoral cooperation networks is considered pertinent for the effective management of professional practices. Therefore, this article is oriented towards the construction of the ideal scenario where a universitygovernmentcompany intersectoral cooperation network can operate on a horizon of 2030. Foresight is used as a research and planning method, in conjunction with the consultation of experts from different social sectors that lead to obtaining sixteen scenarios of probable occurrence. For this, techniques, such as the prospective workshop, Delphi method, structural analysis (MICMAC) and scenario analysis (SMIC), are used. The results show a bet scenario where the four finally ...