Abstract:
Electricity is the most versatile energy carrier in modern economics. There is
a growing tendency in the demand for electricity over the past two decades in
Sri Lanka. Ceylon Electricity Board is the only major utility in Sri Lanka
where electricity is generated for the whole nation. None of the literatures have
used the Auto-Regressive Integrated Moving Average (ARIMA) approach to
model the electricity generation and consumption of Sri Lanka. This motivated
us to study the monthly electricity generation and consumption of Sri Lanka
using ARIMA approach. In this study, monthly data on electricity generation
and consumption (Giga Watt hour) in Sri Lanka was obtained from the Data
Library of Central bank Sri Lanka, during the period of 2000-2019, where the
demand for electricity was dramatically increased in Sri Lanka. The
Objectives of the study were to fit a suitable ARIMA model for monthly
electricity generation and consumption in Sri Lanka and forecast the electricity
demand in Sri Lanka for the near future. Further, three statistical criteria
Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC)
and Mean Squared Error (MSE)) were considered in order to select the best
fitting ARIMA model. Results revealed that ARIMA(1,0,1) ×
(2,1,1)12, and ARIMA(1,1,1) × (2,0,0)12 are the best fitting models for the
monthly electricity generation and consumption respectively. Further, these
chosen ARIMA models can be used to forecast the electricity generation and
consumption in Sri Lanka in the near future.
