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Scale-specific importance of weather variables for explanation of variations of electricity consumption: The case of Prague, Czech Republic

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  • Bašta, Milan
  • Helman, Karel

Abstract

In this paper we explore the relative importance of the outside temperature and sunshine duration for the explanation of variations of electricity consumption in Prague, Czech Republic. An assessment of relative importance is made on various time scales ranging from the shortest ones associated with abrupt changes up to those associated with medium-run changes. Wavelet analysis is used to accomplish this task. We show that relative importance is scale-specific, i.e. depends on the analyzed time scale. Sunshine duration is generally the more important explanatory variable on the shortest time scales and the outside temperature dominates on higher time scales. The reason for the outside temperature being an inferior explanatory variable on the shortest time scales is a low variability of the outside temperature on these time scales and a dampened reaction of electricity consumption to abrupt changes in the outside temperature. Our results show that sunshine duration should be considered relevant when modeling electricity consumption.

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  • Bašta, Milan & Helman, Karel, 2013. "Scale-specific importance of weather variables for explanation of variations of electricity consumption: The case of Prague, Czech Republic," Energy Economics, Elsevier, vol. 40(C), pages 503-514.
  • Handle: RePEc:eee:eneeco:v:40:y:2013:i:c:p:503-514
    DOI: 10.1016/j.eneco.2013.07.023
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    as
    1. Ramsey James B. & Lampart Camille, 1998. "The Decomposition of Economic Relationships by Time Scale Using Wavelets: Expenditure and Income," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 3(1), pages 1-22, April.
    2. Lai, T.M. & To, W.M. & Lo, W.C. & Choy, Y.S., 2008. "Modeling of electricity consumption in the Asian gaming and tourism center—Macao SAR, People's Republic of China," Energy, Elsevier, vol. 33(5), pages 679-688.
    3. James Ramsey, 1999. "Regression over Timescale Decompositions: A Sampling Analysis of Distributional Properties," Economic Systems Research, Taylor & Francis Journals, vol. 11(2), pages 163-184.
    4. Bessec, Marie & Fouquau, Julien, 2008. "The non-linear link between electricity consumption and temperature in Europe: A threshold panel approach," Energy Economics, Elsevier, vol. 30(5), pages 2705-2721, September.
    5. repec:dau:papers:123456789/11438 is not listed on IDEAS
    6. Pardo, Angel & Meneu, Vicente & Valor, Enric, 2002. "Temperature and seasonality influences on Spanish electricity load," Energy Economics, Elsevier, vol. 24(1), pages 55-70, January.
    7. Zachariadis, Theodoros & Pashourtidou, Nicoletta, 2007. "An empirical analysis of electricity consumption in Cyprus," Energy Economics, Elsevier, vol. 29(2), pages 183-198, March.
    8. Egelioglu, F. & Mohamad, A.A. & Guven, H., 2001. "Economic variables and electricity consumption in Northern Cyprus," Energy, Elsevier, vol. 26(4), pages 355-362.
    9. Lam, Joseph C. & Tang, H.L. & Li, Danny H.W., 2008. "Seasonal variations in residential and commercial sector electricity consumption in Hong Kong," Energy, Elsevier, vol. 33(3), pages 513-523.
    10. repec:dau:papers:123456789/8180 is not listed on IDEAS
    11. Pilli-Sihvola, Karoliina & Aatola, Piia & Ollikainen, Markku & Tuomenvirta, Heikki, 2010. "Climate change and electricity consumption--Witnessing increasing or decreasing use and costs?," Energy Policy, Elsevier, vol. 38(5), pages 2409-2419, May.
    12. Psiloglou, B.E. & Giannakopoulos, C. & Majithia, S. & Petrakis, M., 2009. "Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessment," Energy, Elsevier, vol. 34(11), pages 1855-1863.
    13. Nguyen, Hang T. & Nabney, Ian T., 2010. "Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models," Energy, Elsevier, vol. 35(9), pages 3674-3685.
    14. Mohamed, Zaid & Bodger, Pat, 2005. "Forecasting electricity consumption in New Zealand using economic and demographic variables," Energy, Elsevier, vol. 30(10), pages 1833-1843.
    15. Payne, James E., 2010. "A survey of the electricity consumption-growth literature," Applied Energy, Elsevier, vol. 87(3), pages 723-731, March.
    16. Hondroyiannis, George, 2004. "Estimating residential demand for electricity in Greece," Energy Economics, Elsevier, vol. 26(3), pages 319-334, May.
    17. Fox, John, 2005. "The R Commander: A Basic-Statistics Graphical User Interface to R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i09).
    18. Ramsey, James B. & Lampart, Camille, 1998. "Decomposition Of Economic Relationships By Timescale Using Wavelets," Macroeconomic Dynamics, Cambridge University Press, vol. 2(1), pages 49-71, March.
    19. Gençay, Ramazan & Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon J., 2001. "An Introduction to Wavelets and Other Filtering Methods in Finance and Economics," Elsevier Monographs, Elsevier, edition 1, number 9780122796708.
    20. Matteo Manera & Angelo Marzullo, 2003. "Modelling the Load Curve of Aggregate Electricity Consumption Using Principal Components," Working Papers 2003.95, Fondazione Eni Enrico Mattei.
    21. Beccali, M. & Cellura, M. & Lo Brano, V. & Marvuglia, A., 2008. "Short-term prediction of household electricity consumption: Assessing weather sensitivity in a Mediterranean area," Renewable and Sustainable Energy Reviews, Elsevier, vol. 12(8), pages 2040-2065, October.
    22. Soares, Lacir J. & Medeiros, Marcelo C., 2008. "Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data," International Journal of Forecasting, Elsevier, vol. 24(4), pages 630-644.
    23. Ouedraogo, Nadia S., 2013. "Energy consumption and economic growth: Evidence from the economic community of West African States (ECOWAS)," Energy Economics, Elsevier, vol. 36(C), pages 637-647.
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    6. Yukseltan, E. & Kok, A. & Yucekaya, A. & Bilge, A. & Aktunc, E. Agca & Hekimoglu, M., 2022. "The impact of the COVID-19 pandemic and behavioral restrictions on electricity consumption and the daily demand curve in Turkey," Utilities Policy, Elsevier, vol. 76(C).
    7. Ali K k & Erg n Y kseltan & Mustafa Hekimo lu & Esra Agca Aktunc & Ahmet Y cekaya & Ay e Bilge, 2022. "Forecasting Hourly Electricity Demand Under COVID-19 Restrictions," International Journal of Energy Economics and Policy, Econjournals, vol. 12(1), pages 73-85.
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    9. Tarek Atalla, Simona Bigerna, Carlo Andrea Bollino, and Rolando Fuentes, 2017. "Analyzing the Effects of Renewable Energy and Climate Conditions on Consumer Welfare," The Energy Journal, International Association for Energy Economics, vol. 0(KAPSARC S).

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    More about this item

    Keywords

    Electricity consumption; Temperature; Sunshine duration; Wavelet analysis; Time scale;
    All these keywords.

    JEL classification:

    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other

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