| dc.description.abstract | The efficient management of the demand and supply of energy has become one of the main focuses of electric power distribution companies, where the viability of this management is given through a context of modernization and technological advances that has been happening
in an accelerated way in the energy sector. The concept of Smart Grids arises related to the new capabilities of management of intelligent energy networks, through the integration of automated mechanisms of communication that enables the attainment of a global vision of the state of the energy network and all of its components. Thus, companies will have massive volumes of information at their disposal, being capable of being analyzed and sufficient to support the strategy of enhancement of the cycle of production, distribution and commercialization of energy in its entirety. Electricity, as a commodity, has unique properties, for example, the impossibility of being stored efficiently and economically viable, and for this reason, production must satisfy the needs of the load diagram constantly and immediately. In addition to this factor, predicting the consumption demand assumes a fundamental role for the whole electric sector from the moment of contracting the energy until its distribution. The possibility of predicting future events becomes a differential to the point where it will be possible to intervene in advance of certain unexpected events, such as network failures, and to predict energy consumption peaks for certain sectors, making it possible to streamline mechanisms to respond to the needs, or be used in more assertive planning aiming at the sustainable and efficient management of the generation and transmission of energy in relation to the anticipated needs. Thus, the main objective of the present work is the development and testing of a methodology that allows the creation of a predictive short term model of energy consumption in order to make feasible the better management of operations related to electric power grids. Characteristically, the energy consumption presents certain behaviors that can be justified by numerous variables, to cite, temporal dimensions, such as the time of day when the energy is consumed or the season itself. The prediction model will be based on the use of historical data of consumption correlating this to variables that can influence consumption in order to create more assertive and adequate models. | en |
