A Comparative Analysis of Techniques for Forecasting Electricity Consumption

• Main Authors: P., Ozoh, S., Abd-Rahman, J., Labadin, M., Apperley
• Format: Article
• Language: English
• Published: International Journal of Computer Applications 2014
• Subjects: T Technology (General)
• Online Access: http://ir.unimas.my/id/eprint/8465/1/A%20Comparative%20Analysis%20of%20Techniques%20for%20Forecasting%20Electricity%20Consumption%20%28abstract%29.pdf; http://ir.unimas.my/id/eprint/8465/

The issue of obtaining reliable forecasting methods for electricity consumption has been widely discussed by past research work. This is due to the increased demand for electricity and as a result, the development of efficient pricing models. Several techniques have been used in past research for forecasting electricity consumption. This includes the use of forecasting, time-series technique (FTST) and artificial neural networks (ANN). This paper introduces a modified Newton’s model (MNM) to forecast electricity consumption. Forecasting models are developed from historical data and predictive estimates are obtained. This research work utilizes data from Universiti Malaysia Sarawak, a public university in Malaysia, from 2009 to 2012. The variables considered in this research include electricity consumption for different months over the years.