Forecasting electrical demand is currently a discussion subject, but due to its random and stochastic behavior it is very difficult to do. In the present research, a methodology is proposed to predict electricity consumption in the short term using Markov Chains and Monte Carlo, and the results are validated with numerical techniques of curve reconstruction such as least squares and cubic splines, as well as verification of real demand behavior. Finally, the error that the proposed model has is verified against the other alternatives, having it be reduced. As well as, the prediction of electricity demand for a period of 7 days.
|Título traducido de la contribución||Forecasting electrical demand in short term based on markov chains and monte carlo|
|Número de páginas||17|
|Publicación||RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao|
|Estado||Publicada - jun 2020|
Nota bibliográficaPublisher Copyright:
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- Curve Reconstruction
- Demand Forecasting
- Electrical Demand
- Markov Chains