Abstract
This study focus on forecasting the expected consumption for natural gas in Malaysia from years 2011 until 2015, using Univariate Modelling Techniques. It was based on historical data of natural gas consumption from the year 1971 to 2010. Natural gas has always been important natural resources to the country's energy strategic planning. In this study, the annual consumption data was obtained to forecast the demand in natural gas using the Exponential Smoothing Technique. Under this technique, one has to analyse the series of historical values, which provide the opportunity to overcome the problem of shortage for natural gas supply. We also found that the Holt's Winters was the most accurate method when the value of Root Mean Square Error (RMSE) given the smallest amount. This study is important to the country to assess the shortage of supply for natural gas in the future and the need for immediate solutions to overcome it. Currently, the world is experiencing with high demand for natural gas, electricity, renewable energy and nuclear power. Indeed, in Malaysia, the demand for natural gas has been growing drastically over the past few years especially the demand from industrial sector.
Keywords :Natural Gas; UnivariateModelling Techniques; Exponential Smoothing; Root Mean
Square Error (RMSE)
Metadata
Item Type: | Student Project |
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Creators: | Creators Email / ID Num. Syed Badrulzaman, Syarifah Syazana Alqudhsi 2008585665 |
Contributors: | Contribution Name Email / ID Num. Advisor Bujang, Imbarine imbar074@uitm.edu.my Advisor Mohammad, Sheikh Junaidi sheikhju@uitm.edu.my |
Subjects: | Q Science > QD Chemistry > Organic chemistry Q Science > QD Chemistry > Organic chemistry > Oxidation Q Science > QK Botany > Plant physiology > Botanical chemistry. Phytochemicals |
Divisions: | Universiti Teknologi MARA, Sabah > Kota Kinabalu Campus > Faculty of Business and Management |
Programme: | Bachelor of Business Administration (Hons) Business Economics |
Keywords: | Natural gas, univariate modelling techniques, exponential smoothing, root mean square error |
Date: | 2010 |
URI: | https://ir.uitm.edu.my/id/eprint/71898 |
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