Electric Energy Consumption Forecasting Based on Economic Variables in Nakhonratchasima, Thailand

Abstract:

Electric energy is vital for social and economic development. The electric energy consumption forecasting plays an important role for energy management and allocation of resources in the future. In this paper, the influence of economic variables on the annual electric energy consumption in Nakhonratchasima has been investigated. Models are developed by using multiple regression analysis. It is founded that the electric energy consumption correlated with four economic variables, which are gross provincial product (GPP), GPP per capita, the energy sales of liquid petroleum gas (LPG) and high speed diesel usages. The historical electric energy consumption and all variables for the period 2002–2010 have been analyzed in 10 models. The study proposed 5 models for electric energy prediction in 2011. In conclusion, the effective model has been selected by comparison of adjusted R2, mean absolute error (MAE) and root mean squared error (RMSE) of the proposed models. Model 3 is acceptable in relation to electric energy consumption forecasting, with adjusted R2 and RMSE equal to 0.9915 and 1.54% respectively. The results indicate that the model using GPP and diesel usages as variables has strong ability to predict future annual electric energy consumption with 4,202,326,368 kWh in 2011.

• Periodical: Advanced Materials Research (Volume 677)
• Pages: 523-527
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.677.523
• Online since: March 2013
• Authors: Nopphadon Khodpun, Sureeporn Meehom
• Keywords: Economic Variables, Electric Energy Consumption, Forecasting, Multiple Regression, Thailand

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