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Statistical Analysis and Modeling for Detecting Regime Changes in Gas Nomination Time Series

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Operations Research Proceedings 2021 (OR 2021)

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Abstract

As a result of the legislation for gas markets introduced by the European Union in 2005, separate independent companies have to conduct the transport and trading of natural gas. The current gas market of Germany, which has a market value of more than 54 billion USD, consists of Transmission System Operators (TSO), network users, and traders. Traders can nominate a certain amount of gas anytime and anywhere in the network. Such unrestricted access for the traders, on the other hand, increase the uncertainty in the gas supply management. Some customers’ behaviors may cause abrupt structural changes in gas flow time series. In particular, it is a challenging task for the TSO operators to predict gas nominations 6 to 10 h-ahead. In our study, we aim to investigate the regime changes in time series of nominations to predict the 6 to 10 h-ahead of gas nominations.

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References

  1. Brabec, M., et al.: A nonlinear mixed effects model for the prediction of natural gas consumption by individual customers. Int. J. Forecast. 24(4), 659–678 (2008)

    Google Scholar 

  2. Fügenschuh, A.: Mathematical optimization for challenging network planning problems in unbundled liberalized gas markets. Energy Syst. 5(3), 449–473 (2013). https://doi.org/10.1007/s12667-013-0099-8

    Article  Google Scholar 

  3. Open Grid Europe GmbH. https://www.oge.net/

  4. Hamilton, J.D.: A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 47, 357–384 (1989)

    Google Scholar 

  5. Hamilton, J.D.: Regime switching models. In: Durlauf, S.N., Blume, L.E. (eds.) Macroeconometrics and Time Series Analysis. TNPEC, pp. 202–209. Palgrave Macmillan UK, London (2010). https://doi.org/10.1057/9780230280830_23

    Chapter  Google Scholar 

  6. Kim, C.-J.: Dynamic linear models with Markov-switching. J. Econ. 60(1–2), 1–22 (1994)

    Google Scholar 

  7. Kurek, T., Wojdan, K., Swirski, K.: Long-term prediction of underground gas storage user gas flow nominations. J. Power Technol. 99(4) 272–280 (2020)

    Google Scholar 

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Acknowledgement

The work for this article has been conducted within the Research Campus Modal funded by the German Federal Ministry of Education and Research (fund numbers 05M14ZAM, 05M20ZBM).

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Correspondence to Milena Petkovic .

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Petkovic, M., Zakiyeva, N., Zittel, J. (2022). Statistical Analysis and Modeling for Detecting Regime Changes in Gas Nomination Time Series. In: Trautmann, N., Gnägi, M. (eds) Operations Research Proceedings 2021. OR 2021. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-08623-6_29

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