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Forecasting of commercial energy consumption in India using Artificial Neural Network

Author

Listed:
  • S. Jebaraj
  • S. Iniyan
  • Hemanth Kota

Abstract

The forecasting of energy consumption is essential for any country to study the future energy demand and to introduce the necessary government policies. This paper presents the formulation of forecasting models based on the Artificial Neural Network (ANN) for the consumption of conventional energy sources. In India, the total energy consumption for coal, oil, electricity and natural gas would be 1594.84 million tones, 720.69 million tones, 1395754 GWh and 137169.1 million cu.m respectively in the year 2030. The actual consumption data is used to validate the different forecasting models and it is found that the ANN model gives better results in most of the cases.

Suggested Citation

  • S. Jebaraj & S. Iniyan & Hemanth Kota, 2007. "Forecasting of commercial energy consumption in India using Artificial Neural Network," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 27(3), pages 276-301.
    • Handle: RePEc:ids:ijgeni:v:27:y:2007:i:3:p:276-301
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    Cited by:

    1. Shuyu Li & Xuan Yang & Rongrong Li, 2019. "Forecasting Coal Consumption in India by 2030: Using Linear Modified Linear (MGM-ARIMA) and Linear Modified Nonlinear (BP-ARIMA) Combined Models," Sustainability, MDPI, vol. 11(3), pages 1-19, January.
    2. Kumar, Ujjwal & Jain, V.K., 2010. "Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India," Energy, Elsevier, vol. 35(4), pages 1709-1716.

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