A Comparative Analysis of Techniques for Forecasting Electricity Consumption

P., Ozoh and S., Abd-Rahman and J., Labadin and M., Apperley (2014) A Comparative Analysis of Techniques for Forecasting Electricity Consumption. International Journal of Computer Applications, 88 (15). ISSN 0975 – 8887)

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Abstract

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.

Item Type: E-Article
Uncontrolled Keywords: Electricity consumption, electricity forecasting, time-series, artificial neural networks, modified newton’s method, historical data, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 04 Aug 2015 01:05
Last Modified: 04 Aug 2015 01:05
URI: http://ir.unimas.my/id/eprint/8465

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