IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v98y2012icp346-356.html
   My bibliography  Save this article

Relationships between meteorological variables and monthly electricity demand

Author

Listed:
  • Apadula, Francesco
  • Bassini, Alessandra
  • Elli, Alberto
  • Scapin, Simone

Abstract

Electricity demand depends on climatic condition and the influence of weather has been widely reported in the past. The main purpose of this study is to analyse the effect of the meteorological variability on the monthly electricity demand in Italy. Temperature, wind speed, relative humidity and cloud cover are considered; the calendar effect is also taken into account. A multiple linear regression model based on calendar and weather related variables is developed to study the relationships between meteorological variables and electricity demand as well as to predict the monthly electricity demand up to 1month ahead. The model has been extensively tested over the period 1994–2009 using different combinations of the weather related variables. Accuracies obtained are quite similar and range between 0.85% and 0.89%. Temperature turns out to be the most important variable. According to the month considered, a specific combination of the weather related variables can give the lowest Mean Absolute Percentage Error (MAPE) but differences are usually small. Good results for the summer months are obtained using Heat Index to calculate the Cooling Degree-Days; the cloud cover has a major influence from February to April.

Suggested Citation

  • Apadula, Francesco & Bassini, Alessandra & Elli, Alberto & Scapin, Simone, 2012. "Relationships between meteorological variables and monthly electricity demand," Applied Energy, Elsevier, vol. 98(C), pages 346-356.
    • Handle: RePEc:eee:appene:v:98:y:2012:i:c:p:346-356
    DOI: 10.1016/j.apenergy.2012.03.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261912002735
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2012.03.053?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. 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.
    2. Hahn, Heiko & Meyer-Nieberg, Silja & Pickl, Stefan, 2009. "Electric load forecasting methods: Tools for decision making," European Journal of Operational Research, Elsevier, vol. 199(3), pages 902-907, December.
    3. 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.
    4. 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.
    5. repec:dau:papers:123456789/8180 is not listed on IDEAS
    6. Moral-Carcedo, Julian & Vicens-Otero, Jose, 2005. "Modelling the non-linear response of Spanish electricity demand to temperature variations," Energy Economics, Elsevier, vol. 27(3), pages 477-494, May.
    7. Vassileva, Iana & Wallin, Fredrik & Dahlquist, Erik, 2012. "Analytical comparison between electricity consumption and behavioral characteristics of Swedish households in rented apartments," Applied Energy, Elsevier, vol. 90(1), pages 182-188.
    8. Chung, Mo & Park, Hwa-Choon, 2012. "Building energy demand patterns for department stores in Korea," Applied Energy, Elsevier, vol. 90(1), pages 241-249.
    9. Zhu, Suling & Wang, Jianzhou & Zhao, Weigang & Wang, Jujie, 2011. "A seasonal hybrid procedure for electricity demand forecasting in China," Applied Energy, Elsevier, vol. 88(11), pages 3807-3815.
    10. 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.
    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. Moral-Carcedo, Julián & Pérez-García, Julián, 2015. "Temperature effects on firms’ electricity demand: An analysis of sectorial differences in Spain," Applied Energy, Elsevier, vol. 142(C), pages 407-425.
    2. 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.
    3. Chabouni, Naima & Belarbi, Yacine & Benhassine, Wassim, 2020. "Electricity load dynamics, temperature and seasonality Nexus in Algeria," Energy, Elsevier, vol. 200(C).
    4. Miller, J. Isaac & Nam, Kyungsik, 2022. "Modeling peak electricity demand: A semiparametric approach using weather-driven cross-temperature response functions," Energy Economics, Elsevier, vol. 114(C).
    5. Ozhegov, Evgeniy & Popova, Evgeniya, 2017. "Demand for electricity and weather conditions: Nonparametric analysis," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 55-73.
    6. Wang, Yaoping & Bielicki, Jeffrey M., 2018. "Acclimation and the response of hourly electricity loads to meteorological variables," Energy, Elsevier, vol. 142(C), pages 473-485.
    7. Lee, Chien-Chiang & Chiu, Yi-Bin, 2011. "Electricity demand elasticities and temperature: Evidence from panel smooth transition regression with instrumental variable approach," Energy Economics, Elsevier, vol. 33(5), pages 896-902, September.
    8. Kang, Jieyi & Reiner, David M., 2022. "What is the effect of weather on household electricity consumption? Empirical evidence from Ireland," Energy Economics, Elsevier, vol. 111(C).
    9. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    10. Do, Linh Phuong Catherine & Lin, Kuan-Heng & Molnár, Peter, 2016. "Electricity consumption modelling: A case of Germany," Economic Modelling, Elsevier, vol. 55(C), pages 92-101.
    11. 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.
    12. Jaume Rosselló Nadal & Mohcine Bakhat, 2009. "A new approach to estimating tourism-induced electricity consumption," CRE Working Papers (Documents de treball del CRE) 2009/6, Centre de Recerca Econòmica (UIB ·"Sa Nostra").
    13. Palacios-Garcia, E.J. & Moreno-Munoz, A. & Santiago, I. & Flores-Arias, J.M. & Bellido-Outeirino, F.J. & Moreno-Garcia, I.M., 2018. "A stochastic modelling and simulation approach to heating and cooling electricity consumption in the residential sector," Energy, Elsevier, vol. 144(C), pages 1080-1091.
    14. Gupta, Eshita, 2012. "Global warming and electricity demand in the rapidly growing city of Delhi: A semi-parametric variable coefficient approach," Energy Economics, Elsevier, vol. 34(5), pages 1407-1421.
    15. 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.
    16. Hekkenberg, M. & Benders, R.M.J. & Moll, H.C. & Schoot Uiterkamp, A.J.M., 2009. "Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands," Energy Policy, Elsevier, vol. 37(4), pages 1542-1551, April.
    17. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
    18. Du, Kerui & Yu, Ying & Wei, Chu, 2020. "Climatic impact on China's residential electricity consumption: Does the income level matter?," China Economic Review, Elsevier, vol. 63(C).
    19. Hekkenberg, M. & Moll, H.C. & Uiterkamp, A.J.M. Schoot, 2009. "Dynamic temperature dependence patterns in future energy demand models in the context of climate change," Energy, Elsevier, vol. 34(11), pages 1797-1806.
    20. Hirano, Y. & Fujita, T., 2012. "Evaluation of the impact of the urban heat island on residential and commercial energy consumption in Tokyo," Energy, Elsevier, vol. 37(1), pages 371-383.

    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:appene:v:98:y:2012:i:c:p:346-356. 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/wps/find/journaldescription.cws_home/405891/description#description .

    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.