Resumen

GIL VERA, Víctor Daniel. MONTHLY FORECAST OF ELECTRICITY DEMAND WITH TIME SERIES. Rev.EIA.Esc.Ing.Antioq [online]. 2016, n.26, pp.111-120. ISSN 1794-1237.

The high volatility of electricity prices has motivated researchers and academics to design models that will enable the forecast of electricity demand in short, medium and long terms. This paper presents a model for forecasting the monthly electricity demand based on time series. The model uses the electricity demand values of Colombia's National Interconnected System (NIS) for the 2008-2014 period as its base. It was concluded that the time series applied to the electricity demand forecast enable a high accuracy level of prediction of future electricity demands (GWh), information which can lead to advantages for producers, distributors and large consumers when establishing strategies, streamlining operations and reaching bilateral agreements.

Palabras clave : Energy markets; Forecasting models; Monthly electricity demand; Time series.

        · resumen en Español | Portugués     · texto en Español | Inglés     · Español ( pdf ) | Inglés ( pdf )