abstract
One of the most desired aspects for power suppliers is the acquisition/sell of energy in a future time. This paper presents a study for power supply forecasting of the residential class, based on time series methods and neural networks, considering short and long term forecast, both of great importance for power suppliers in order to define the future power consumption of a given region.
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Conde, G.A., De Santana, Á.L., FrancÊs, C.L., Rocha, C.A., Rego, L., Gato, V. (2008). Comparative studies of Statistical and Neural Networks Models for Short and Long Term Load Forecasting: a Case Study in the Brazilian Amazon Power Suppliers. In: Ellis, R., Allen, T., Petridis, M. (eds) Applications and Innovations in Intelligent Systems XV. SGAI 2007. Springer, London. https://doi.org/10.1007/978-1-84800-086-5_20
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DOI: https://doi.org/10.1007/978-1-84800-086-5_20
Publisher Name: Springer, London
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