Time series performance for electricity load demand in Johor

Abstract

Development country such as Malaysia need a lot of total amount electricity consumption for economic development and improvement of country. Load demand forecasting is vital to predict electricity consumption and obtain sustainable development. This paper introduces the performance of four types of time series models. Four types of time series models were considered, which are Exponential Smoothing (ES) State Space, Box-Jenkins Autoregressive Integrated Moving Average (ARIMA), Autoregressive Autoregressive (ARAR), and Autoregressive Moving Average Error, Trends and Seasonal Components (TBATS). Using the Root Mean Square Error (RMSE) as the forecast accuracy measure, the study concluded that Exponential Smoothing (ES) State Space was the most appropriate model.