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Univariate time-series forecasting of monthly peak demand of electricity in northern India

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  • Sajal Ghosh

Abstract

This study forecasts the monthly peak demand of electricity in the northern region of India using univariate time-series techniques namely Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) and Holt-Winters Multiplicative Exponential Smoothing (ES) for seasonally unadjusted monthly data spanning from April 2000 to February 2007. In-sample forecasting reveals that the MSARIMA model outperforms the ES model in terms of lower root mean square error, mean absolute error and mean absolute percent error criteria. It has been found that ARIMA (2, 0, 0) (0, 1, 1)12 is the best fitted model to explain the monthly peak demand of electricity, which has been used to forecast the monthly peak demand of electricity in northern India, 15 months ahead from February 2007. This will help Northern Regional Load Dispatch Centre to make necessary arrangements a priori to meet the future peak demand.

Suggested Citation

  • Sajal Ghosh, 2008. "Univariate time-series forecasting of monthly peak demand of electricity in northern India," International Journal of Indian Culture and Business Management, Inderscience Enterprises Ltd, vol. 1(4), pages 466-474.
    • Handle: RePEc:ids:ijicbm:v:1:y:2008:i:4:p:466-474
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    Citations

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    Cited by:

    1. Chaturvedi, Shobhit & Rajasekar, Elangovan & Natarajan, Sukumar & McCullen, Nick, 2022. "A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India," Energy Policy, Elsevier, vol. 168(C).
    2. Rallapalli, Srinivasa Rao & Ghosh, Sajal, 2012. "Forecasting monthly peak demand of electricity in India—A critique," Energy Policy, Elsevier, vol. 45(C), pages 516-520.
    3. Krzysztof Karpio & Piotr Łukasiewicz & Rafik Nafkha, 2023. "New Method of Modeling Daily Energy Consumption," Energies, MDPI, vol. 16(5), pages 1-24, February.
    4. Majumder, Rajarshi & Ghosh, Subhadip & Chatterjee, Bidisha, 2022. "Energy infrastructure in India: challenges and opportunities," MPRA Paper 120106, University Library of Munich, Germany.

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