IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/8899.html
   My bibliography  Save this paper

Forecasting Demand for Electricity: Some Methodological Issues and an Analysis

Author

Listed:
  • Pillai N., Vijayamohanan

Abstract

Electricity demand projection is of utmost importance as electricity has become a vital input to the wellbeing of any society, driving the demand for it from an ever-expanding set of diverse needs to grow on an increasing rate, which in turn places increasing demands on scarce resources of capital investment, material means, and man-power. More specifically, the continuing ‘energy crisis’ has made crucial the need for accurate projection of electricity demand; hence the importance of the forecasting methods. The present paper critically evaluates the electricity demand forecasting methodology and proposes a methodology in the classical time series framework.

Suggested Citation

  • Pillai N., Vijayamohanan, 2008. "Forecasting Demand for Electricity: Some Methodological Issues and an Analysis," MPRA Paper 8899, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:8899
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/8899/1/MPRA_paper_8899.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. N. Vijayamohanan Pillai, 2001. "Electricity demand analysis and forecasting: The tradition is questioned," Centre for Development Studies, Trivendrum Working Papers 312, Centre for Development Studies, Trivendrum, India.
    2. Lester D. Taylor, 1975. "The Demand for Electricity: A Survey," Bell Journal of Economics, The RAND Corporation, vol. 6(1), pages 74-110, Spring.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Olmstead, Sheila M. & Michael Hanemann, W. & Stavins, Robert N., 2007. "Water demand under alternative price structures," Journal of Environmental Economics and Management, Elsevier, vol. 54(2), pages 181-198, September.
    2. Céline Nauges & Arnaud Reynaud, 2001. "Estimation de la demande domestique d'eau potable en France," Revue Économique, Programme National Persée, vol. 52(1), pages 167-185.
    3. Acuña, Guillermo, 2017. "Elasticidades de la demanda de agua en Chile [Elasticities of water demand in Chile]," MPRA Paper 82916, University Library of Munich, Germany.
    4. Dergiades, Theologos & Tsoulfidis, Lefteris, 2008. "Estimating residential demand for electricity in the United States, 1965-2006," Energy Economics, Elsevier, vol. 30(5), pages 2722-2730, September.
    5. Massimo Filippini & Bettina Hirl & Giuliano Masiero, 2015. "Rational habits in residential electricity demand," IdEP Economic Papers 1506, USI Università della Svizzera italiana.
    6. Gautam, Tej K. & Paudel, Krishna P., 2018. "The demand for natural gas in the Northeastern United States," Energy, Elsevier, vol. 158(C), pages 890-898.
    7. Fell, Harrison & Li, Shanjun & Paul, Anthony, 2014. "A new look at residential electricity demand using household expenditure data," International Journal of Industrial Organization, Elsevier, vol. 33(C), pages 37-47.
    8. Ivan Faiella & Luciano Lavecchia, 2021. "Households' energy demand and the effects of carbon pricing in Italy," Questioni di Economia e Finanza (Occasional Papers) 614, Bank of Italy, Economic Research and International Relations Area.
    9. Henry Lim & Glenn Jenkins, 2000. "Electricity Demand And Electricity Value," Development Discussion Papers 2000-01, JDI Executive Programs.
    10. Kevin Neels, 1982. "Reducing Energy Consumption in Housing: An Assessment of Alternatives," International Regional Science Review, , vol. 7(1), pages 69-81, May.
    11. Pillai N., Vijayamohanan, 2008. "Strengthening Infrastructure: Power Sector Reforms- Some Viable Proposals For Kerala," MPRA Paper 8869, University Library of Munich, Germany.
    12. Fullerton, Thomas M. & Juarez, David A. & Walke, Adam G., 2012. "Residential electricity consumption in Seattle," Energy Economics, Elsevier, vol. 34(5), pages 1693-1699.
    13. Renwick, Mary E. & Green, Richard D., 2000. "Do Residential Water Demand Side Management Policies Measure Up? An Analysis of Eight California Water Agencies," Journal of Environmental Economics and Management, Elsevier, vol. 40(1), pages 37-55, July.
    14. Bai, Y. & Dahl, C.A. & Zhou, D.Q. & Zhou, P., 2014. "Stockpile strategy for China׳s emergency oil reserve: A dynamic programming approach," Energy Policy, Elsevier, vol. 73(C), pages 12-20.
    15. Miguel Bacharach & William J. Vaughan, 1994. "Household Water Demand Estimation," IDB Publications (Working Papers) 25218, Inter-American Development Bank.
    16. Filippini, Massimo & Hirl, Bettina & Masiero, Giuliano, 2018. "Habits and rational behaviour in residential electricity demand," Resource and Energy Economics, Elsevier, vol. 52(C), pages 137-152.
    17. Woo, C.K. & Liu, Y. & Zarnikau, J. & Shiu, A. & Luo, X. & Kahrl, F., 2018. "Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016," Applied Energy, Elsevier, vol. 222(C), pages 460-474.
    18. Brühl, Johanna & Smith, Grant & Visser, Martine, 2019. "Simple is good: Redesigning utility bills to reduce complexity and increase understanding," Utilities Policy, Elsevier, vol. 60(C), pages 1-1.
    19. Maddigan, Ruth J. & Chern, Wen S. & Gallagher, Colleen A., 1980. "Irrigation And The Demand For Electricity," 1980 Annual Meeting, July 27-30, Urbana-Champaign, Illinois 278920, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    More about this item

    Keywords

    Electricity demand; Forecasting; Kerala; Time series analysis;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:8899. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.