Forecasting of Production and Consumption of Ethanol in Thailand Using Time Series Analysis

Sasiwimon Sriyotha; Rojanee Homchalee; Weerapat Sessomboon

doi:10.4028/www.scientific.net/AMM.781.651

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 781Forecasting of Production and Consumption of...

Forecasting of Production and Consumption of Ethanol in Thailand Using Time Series Analysis

Abstract:

Ethanol is the important renewable energy in Thailand. It is alcohol produced from sugarcane and tapioca that are agricultural products available in Thailand. Ethanol is used to blend with gasoline for use as gasohol. Ethanol production and consumption in Thailand are fluctuating. Consequently, planning of ethanol production and consumption is irrelevant. In order to solve this problem, this study aims to find forecasting models using time series analysis including exponential smoothing and the Box-Jenkins methods. The most appropriate forecasting model was selected from the two methods by considering the minimum of the mean absolute percentage error: MAPE. It was found that the Box-Jenkins is the most appropriate method to forecast both ethanol production and consumption. The forecasting results were then used to determine appropriate quantity and proportion of molasses and tapioca needed for ethanol production in the future.

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Periodical:

Applied Mechanics and Materials (Volume 781)

Pages:

651-654

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.781.651

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Online since:

August 2015

Authors:

Sasiwimon Sriyotha, Rojanee Homchalee, Weerapat Sessomboon*

Keywords:

Box-Jenkins, Ethanol, Exponential Smoothing, Forecasting, Time Series Analysis

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References

[1] www. dede. go. th Alternative Energy Development Plan: AEDP 2012-(2021).

Google Scholar

[2] www. dede. go. th Department of alternative energy development and efficiency. Ministry of energy.

Google Scholar

[3] R. Fildes and S. Makridakis, The impact of empirical accuracy studies on time series analysis and forecasting, International Statistical Review, 63 (1995), 289-308.

DOI: 10.2307/1403481

Google Scholar

[4] Ruey S. Tsay, Time Series and Forecasting : Brief History and Future Research. Journal of the American Statistical Association, 95 (2000), 638-643.

DOI: 10.1080/01621459.2000.10474241

Google Scholar

[5] S. Mahan and S. Vedula, Multiplicative Seasonal Arima Model for Longterm Foreceasting of Inflow. Water Resource Managememt, 9 (1995), 115-126.

DOI: 10.1007/bf00872463

Google Scholar

[6] Statistics on bio-fuel data based collected from department of development and conservation of renewable energy http: /www. biofueldede. com.

Google Scholar