Abstract:
The demand for the electricity in Sri Lanka depends mainly on the activities of domestic,
industrial, and commercial sectors. Electricity has become the most important source of
energy in the domestic sector of the country that is desirous of achieving the newly
developed nation status. This study aims to identify a model to forecast Electricity
demand. The unpredictable changes in the activities cause the demand of electricity to
change unusually. This makes predicting the demand very difficult sometimes. Therefore
in this research the way of incorporating changes in the activities in the time series model
for forecasting is used, which is known as Bayesian Forecasting (BF) model. The
Comparison of this model with the Autoregressive Integrated Moving averages (ARIMA)
model, which is generally used, was made. According to the calculated mean absolute
percentages error (MAPE), BF model gave better performance in term of higher degrees
accuracy of forecasting. Thus on one hand it is encouraging that the Sri Lanka electricity
authorities can have some faith in the model used for forecasting. Hence the chosen
econometric work does have a considerable impact of the policy decisions in the Sri
Lankan electricity supply industry.
