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Short-run electricity demand forecasts in Maharashtra

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  • Sajal Ghosh
  • Anjana Das

Abstract

This paper, has tried to forecast monthly maximum electricity demand for the state Maharashtra, India, using Multiplicative Seasonal Autoregressive Integrated Moving Average (MSARIMA) method for seasonally unadjusted monthly data spanning from April 1980 to June 1999. The forecasted period is 18 months ahead from June 1999. This study's basic findings are that the series does not reveal any drastic change for the forecasted period. It continues to follow the same trend along with the seasonal variation.

Suggested Citation

  • Sajal Ghosh & Anjana Das, 2002. "Short-run electricity demand forecasts in Maharashtra," Applied Economics, Taylor & Francis Journals, vol. 34(8), pages 1055-1059.
    • Handle: RePEc:taf:applec:v:34:y:2002:i:8:p:1055-1059
    DOI: 10.1080/00036840110064656
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    References listed on IDEAS

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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. Mohammad Nure Alam, 2021. "Accessing the Effect of Renewables on the Wholesale Power Market," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 341-360.

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