Systematic review of literature on electrical energy consumption forecast models
DOI:
https://doi.org/10.22395/rium.v19n36a6Keywords:
forecast, energy consumption, short term, long term, neural networksAbstract
The growing consumption of electrical energy, climate change and the development of new technologies demand improvements for efficient energy management. An adequate forecast of the energy consumption is relevant for the sustainable development of any country. This article proposes a systematic review of selected literature based on search chains formed by the terms forecasting, energy and consumption
applied to the scientific databases. In the article are compared mostly the models/ techniques used, the considered variables and the error metrics used for obtaining knowledge on each one of the proposals, relieve its features and thus highlight the void in the literature that might be determinant for new research work. As conclusions are made evident the continuous use of neural networks for forecasting the
energy consumption, the importance of determining the input variables and the error measuring for evaluating the precision of the models. Finally, the development of a model for the CEE short term forecast of a Latin-American developing country based on the comparison and evaluation of different techniques/models, variables and already existing tools is proposed as a new line of research.
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