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Energy Consumption Forecasting for Power Supply Companies

Author

Listed:
  • Irina A. Firsova

    (Financial University under the Government of the Russian Federation, Moscow, Russia)

  • Dinara G. Vasbieva

    (Financial University under the Government of the Russian Federation, Moscow, Russia)

  • Nikolay N. Kosarenko

    (Plekhanov Russian University of Economics, Moscow, Russia,)

  • Maria A. Khvatova

    (Bauman Moscow State Technical University (National Research University), Moscow, Russia,)

  • Lev R. Klebanov

    (Peoples Friendship University of Russia (RUDN), Moscow, Russia.)

Abstract

The paper investigates an issue of the accuracy of energy consumption forecasts for power supply companies, which are an intermediary between the wholesale energy market and the end user. Therefore, the purchased amount of energy should be equal to the predicted one with the least error. In case of any deviations, there is a problem of unsold amounts of energy or its shortage, which leads to financial losses, as the companies have to purchase or sell excessively the purchased energy at the price that is unprofitable for them in the wholesale market. Planning and monitoring the process of energy distribution are essential to achieving accurate energy consumption forecasting, which is an important component of all measures to optimize energy costs. The application of the statistical methods underlying the mathematical forecast models, which describe the process under study, will allow reducing the time for making managerial decisions and increasing the accuracy of energy consumption forecasts, thereby affecting the cost reduction in the power supply company.

Suggested Citation

  • Irina A. Firsova & Dinara G. Vasbieva & Nikolay N. Kosarenko & Maria A. Khvatova & Lev R. Klebanov, 2019. "Energy Consumption Forecasting for Power Supply Companies," International Journal of Energy Economics and Policy, Econjournals, vol. 9(1), pages 1-6.
    • Handle: RePEc:eco:journ2:2019-01-1
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    References listed on IDEAS

    as
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    3. Ewing, Bradley T. & Payne, James E. & Caporin, Massimilano, 2022. "The Asymmetric Impact of Oil Prices and Production on Drilling Rig Trajectory: A correction," Resources Policy, Elsevier, vol. 79(C).
    4. Suat Ozturk & Feride Ozturk, 2018. "Forecasting Energy Consumption of Turkey by Arima Model," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 8(2), pages 52-60, February.
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    Cited by:

    1. Ademola Abdulkareem & E. J. Okoroafor & Ayokunle Awelewa & Aderibigbe Adekitan, 2019. "Pseudo-Inverse Matrix Model for Estimating Long-Term Annual Peak Electricity Demand: The Covenant University s Experience," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 103-109.

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    More about this item

    Keywords

    energy market; energy consumption forecasting; mathematical forecast models; power supply company.;
    All these keywords.

    JEL classification:

    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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