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Statistical models for disaggregation and reaggregation of natural gas consumption data

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  • M. Brabec
  • O. Kon�r
  • M. Malý
  • I. Kasanický
  • E. Pelik�n

Abstract

In this paper, we present a unified framework for natural gas consumption modeling and forecasting. This consists of models of GAM class and their nonlinear extension, tailored for easy estimation, aggregation and treatment of the delayed relationship between temperature and consumption. Since the consumption data for households and small commercial customers are routinely available in many countries only as long-term sum meter readings, their disaggregation and possibly reaggregation to different time intervals is necessary for a variety of purposes. We show some examples of specific models based on the presented framework and then we demonstrate their use in practice, especially for the disaggregation and reaggregation tasks.

Suggested Citation

  • M. Brabec & O. Kon�r & M. Malý & I. Kasanický & E. Pelik�n, 2015. "Statistical models for disaggregation and reaggregation of natural gas consumption data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(5), pages 921-937, May.
    • Handle: RePEc:taf:japsta:v:42:y:2015:i:5:p:921-937
    DOI: 10.1080/02664763.2014.993365
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    References listed on IDEAS

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    Cited by:

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    2. Paulescu, Marius & Brabec, Marek & Boata, Remus & Badescu, Viorel, 2017. "Structured, physically inspired (gray box) models versus black box modeling for forecasting the output power of photovoltaic plants," Energy, Elsevier, vol. 121(C), pages 792-802.
    3. Askari, S. & Montazerin, N. & Fazel Zarandi, M.H., 2016. "Gas networks simulation from disaggregation of low frequency nodal gas consumption," Energy, Elsevier, vol. 112(C), pages 1286-1298.

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