IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v24y2002i1p55-70.html
   My bibliography  Save this article

Temperature and seasonality influences on Spanish electricity load

Author

Listed:
  • Pardo, Angel
  • Meneu, Vicente
  • Valor, Enric

Abstract

No abstract is available for this item.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:eneeco:v:24:y:2002:i:1:p:55-70
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(01)00082-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jose Ramon Cancelo & Antoni Espasa, 1996. "Modelling and forecastng daily series of electricity demand," Investigaciones Economicas, Fundación SEPI, vol. 20(3), pages 359-376, September.
    2. Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
    3. Peirson, John & Henley, Andrew, 1994. "Electricity load and temperature : Issues in dynamic specification," Energy Economics, Elsevier, vol. 16(4), pages 235-243, October.
    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. Mirasgedis, S. & Sarafidis, Y. & Georgopoulou, E. & Lalas, D.P. & Moschovits, M. & Karagiannis, F. & Papakonstantinou, D., 2006. "Models for mid-term electricity demand forecasting incorporating weather influences," Energy, Elsevier, vol. 31(2), pages 208-227.
    2. Hipòlit Torró, 2007. "Forecasting Weekly Electricity Prices at Nord Pool," Working Papers 2007.88, Fondazione Eni Enrico Mattei.
    3. Auffhammer, Maximilian & Mansur, Erin T., 2014. "Measuring climatic impacts on energy consumption: A review of the empirical literature," Energy Economics, Elsevier, vol. 46(C), pages 522-530.
    4. Torro, Hipolit, 2009. "Assessing the influence of spot price predictability on electricity futures hedging," MPRA Paper 18892, University Library of Munich, Germany.
    5. Matthias Ritter, 2012. "Can the market forecast the weather better than meteorologists?," SFB 649 Discussion Papers SFB649DP2012-067, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    6. Curtis, John & Lynch, Muireann Á. & Zubiate, Laura, 2016. "The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland," Energy Economics, Elsevier, vol. 58(C), pages 186-198.
    7. Yau, Y.H. & Pean, H.L., 2011. "The climate change impact on air conditioner system and reliability in Malaysia—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4939-4949.
    8. Cristina Miranda & Reinaldo Castro Souza & Mônica Barros & Cristina Vidigal Cabral de Miranda, 2007. "Short Term Demand Forecasting Using Double Exponential Smoothing and Interventions to Account for Holidays and Temperature Effects," EcoMod2007 23900058, EcoMod.
    9. 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.
    10. Burillo, Daniel & Chester, Mikhail V. & Pincetl, Stephanie & Fournier, Eric, 2019. "Electricity infrastructure vulnerabilities due to long-term growth and extreme heat from climate change in Los Angeles County," Energy Policy, Elsevier, vol. 128(C), pages 943-953.
    11. Cancelo, José Ramón & Espasa, Antoni & Grafe, Rosmarie, 2008. "Forecasting the electricity load from one day to one week ahead for the Spanish system operator," International Journal of Forecasting, Elsevier, vol. 24(4), pages 588-602.
    12. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2016. "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 206-216.
    13. Hongliang Zhang & Jianhong E. Mu & Bruce A. McCarl & Jialing Yu, 2022. "The impact of climate change on global energy use," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(1), pages 1-19, January.
    14. Toparlar, Y. & Blocken, B. & Maiheu, B. & van Heijst, G.J.F., 2018. "Impact of urban microclimate on summertime building cooling demand: A parametric analysis for Antwerp, Belgium," Applied Energy, Elsevier, vol. 228(C), pages 852-872.
    15. Askari, S. & Montazerin, N. & Zarandi, M.H. Fazel, 2015. "Forecasting semi-dynamic response of natural gas networks to nodal gas consumptions using genetic fuzzy systems," Energy, Elsevier, vol. 83(C), pages 252-266.
    16. Lu Jiang & Xingpeng Chen & Bing Xue, 2019. "Features, Driving Forces and Transition of the Household Energy Consumption in China: A Review," Sustainability, MDPI, vol. 11(4), pages 1-20, February.
    17. Sailor, David J, 2001. "Relating residential and commercial sector electricity loads to climate—evaluating state level sensitivities and vulnerabilities," Energy, Elsevier, vol. 26(7), pages 645-657.
    18. repec:qut:auncer:wp103 is not listed on IDEAS
    19. 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.
    20. Rachid Boutti & El Amri Adil & Florence Rodhain, 2019. "Multivariate Analysis of a Time Series EU ETS: Methods and Applications in Carbon Finance," Post-Print hal-03676358, HAL.
    21. Mestekemper, Thomas & Kauermann, Göran & Smith, Michael S., 2013. "A comparison of periodic autoregressive and dynamic factor models in intraday energy demand forecasting," International Journal of Forecasting, Elsevier, vol. 29(1), pages 1-12.

    More about this item

    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:eee:eneeco:v:24:y:2002:i:1:p:55-70. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eneco .

    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.