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Forecasting Hourly Prices in Indian Spot Electricity Market

Author

Listed:
  • Mukherjee, Paramita
  • Coondoo, Dipankor
  • Lahiri, Poulomi

Abstract

In this paper, an attempt has been made to forecast the hourly electricity spot prices in India as this is very important for the bidders in the energy exchange for participating in the day-ahead market. Forecasting high frequency data is a challenging task. In forecasting, different variants of ARMA, ARMA-GARCH models are applied in different contexts, but no unequivocal dominance of a particular model exists. In this paper, based on hourly data for several years for all the regions in India, several variants of ARMAX models are estimated, by combining static and dynamic forecasts. Along with ARMA, intra-day, inter-day and hourly variations in prices as well as seasonalities on weekdays, holidays and festive days are incorporated. ARMAX models in this context performed quite well for forecasting horizons of hourly prices of upto 5 days. Interestingly, the ARMAX models provide reasonably good forecasts for day-ahead-market and the simple structure can be quite easily implemented. Such forecasts are not only essential for the players in the spot market, but also provides insights for policymakers as it reveals several aspects of Indian electricity market including the different dimensions of seasonality in demand.

Suggested Citation

  • Mukherjee, Paramita & Coondoo, Dipankor & Lahiri, Poulomi, 2019. "Forecasting Hourly Prices in Indian Spot Electricity Market," MPRA Paper 103161, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:103161
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Forecasting; electricity; hourly data; energy; spot price; ARMAX model; day-ahead market;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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