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A statistical model for the estimation of natural gas consumption

Author

Listed:
  • Vondrácek, Jirí
  • Pelikán, Emil
  • Konár, Ondrej
  • Cermáková, Jana
  • Eben, Krystof
  • Malý, Marek
  • Brabec, Marek

Abstract

In this paper we present a statistical approach to natural gas consumption estimation of individual residential and small commercial customers. The approach is based on nonlinear regression principles. Parameters are estimated using mainly two real data sets - ordinary (approximately annual) meter readings of almost all customers and additional (approximately monthly) meter readings designed and operated within the frame of cooperation between the Institute of Computer Science of the Czech Academy of Sciences (ICS) and the West Bohemian Gas Distribution Company, a part of the RWE Group (WBG). The model was tested on various data sets. It has broad applicability in many areas of gas industry.

Suggested Citation

  • Vondrácek, Jirí & Pelikán, Emil & Konár, Ondrej & Cermáková, Jana & Eben, Krystof & Malý, Marek & Brabec, Marek, 2008. "A statistical model for the estimation of natural gas consumption," Applied Energy, Elsevier, vol. 85(5), pages 362-370, May.
    • Handle: RePEc:eee:appene:v:85:y:2008:i:5:p:362-370
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    4. Marta P. Fernandes & Joaquim L. Viegas & Susana M. Vieira & João M. C. Sousa, 2017. "Segmentation of Residential Gas Consumers Using Clustering Analysis," Energies, MDPI, vol. 10(12), pages 1-26, December.
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    9. Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2014. "Scenario analysis of nonresidential natural gas consumption in Italy," Applied Energy, Elsevier, vol. 113(C), pages 392-403.
    10. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
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    15. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
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    17. Ayşe Özmen, 2023. "Sparse regression modeling for short- and long‐term natural gas demand prediction," Annals of Operations Research, Springer, vol. 322(2), pages 921-946, March.
    18. Azadeh, A. & Asadzadeh, S.M. & Saberi, M. & Nadimi, V. & Tajvidi, A. & Sheikalishahi, M., 2011. "A Neuro-fuzzy-stochastic frontier analysis approach for long-term natural gas consumption forecasting and behavior analysis: The cases of Bahrain, Saudi Arabia, Syria, and UAE," Applied Energy, Elsevier, vol. 88(11), pages 3850-3859.
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