Aplicação de redes neurais artificiais à previsão do preço da energia elétrica para distintas zonas de mercados desregulamentados
Resumo
The estimation of the energy price plays a crucial role in the current model of
commercialization of energy in many countries. Better estimation capacity makes it
possible to identify appropriate strategies for market players. Thus, this work aims to
determine a methodology to estimate point values and intervals (maximum and minimum)
for a day for the Pennsylvania - New Jersey - Maryland energy market through Data Mining,
where they will be considered Attribute Selectors and Artificial Neural Networks. In this
sense, the responses of neural networks of the Multilayer Perceptron type and of Recurrent
Neural Networks will be analyzed, considering different topologies.
Keywords: Energy market, Artificial neural networks, Energy Price, Time-series forecasting.
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