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Enfoque UTE

On-line version ISSN 1390-6542Print version ISSN 1390-9363


ALEAGA, Arlys Michel Lastre; GARCES, Erik Fernando Méndez  and  GARCIA, Alexis Cordovés. Automated system for load flow prediction in power substations using artificial neural networks. Enfoque UTE [online]. 2015, vol.6, n.3, pp.20-35. ISSN 1390-6542.

The load flow is of great importance in assisting the process of decision making and planning of generation, distribution and transmission of electricity. Ignorance of the values in this indicator, as well as their inappropriate prediction, difficult decision making and efficiency of the electricity service, and can cause undesirable situations such as; the on demand, overheating of the components that make up a substation, and incorrect planning processes electricity generation and distribution. Given the need for prediction of flow of electric charge of the substations in Ecuador this research proposes the concept for the development of an automated prediction system employing the use of Artificial Neural Networks.

Keywords : Prediction; Electric Charge; Artificial Neural Networks..

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