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Application of Sarima Model in Load Forecasting in Hanoi City

Author

Listed:
  • Duong Trung Kien

    (Faculty of Energy and Industry Management, Electric Power University, Hanoi, Vietnam,)

  • Phan Dieu Huong

    (School of Economics and Management, Hanoi University of Science and Technology, Vietnam)

  • Nguyen Dat Minh

    (Faculty of Energy and Industry Management, Electric Power University, Hanoi, Vietnam,)

Abstract

Many countries and researchers are interested in load forecasting due to its significance. The results of load forecasting are an indispensable basis for electricity planning and investment plan for the power system in the future. In addition, short-term load forecasting is also a mandatory requirement in proactively developing business and system operation plan of units in power sector. When the SARIMA(p,d,q)(P,D,Q)S model is used for load forecasting in Hanoi, the results ensure forecast accuracy, feasibility of available data as well as the software's ease of use. SARIMA model can also be used in load forecasting in other provinces and cities in Vietnam or used for electricity forecasting. With the research sample from 2019 to 2021, the model SARIMA(0,1,6)(0.1,1)24 and (0,1,7)(0.1,1) 24 are used for short-term load forecasting in term of typical working day and day-off in Hanoi.

Suggested Citation

  • Duong Trung Kien & Phan Dieu Huong & Nguyen Dat Minh, 2023. "Application of Sarima Model in Load Forecasting in Hanoi City," International Journal of Energy Economics and Policy, Econjournals, vol. 13(3), pages 164-170, May.
    • Handle: RePEc:eco:journ2:2023-03-20
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Energy consumption; Load Forecast; model SARIMA.;
    All these keywords.

    JEL classification:

    • L5 - Industrial Organization - - Regulation and Industrial Policy
    • O2 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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