IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1402.7027.html
   My bibliography  Save this paper

Efficient Modeling and Forecasting of the Electricity Spot Price

Author

Listed:
  • Florian Ziel
  • Rick Steinert
  • Sven Husmann

Abstract

The increasing importance of renewable energy, especially solar and wind power, has led to new forces in the formation of electricity prices. Hence, this paper introduces an econometric model for the hourly time series of electricity prices of the European Power Exchange (EPEX) which incorporates specific features like renewable energy. The model consists of several sophisticated and established approaches and can be regarded as a periodic VAR-TARCH with wind power, solar power, and load as influences on the time series. It is able to map the distinct and well-known features of electricity prices in Germany. An efficient iteratively reweighted lasso approach is used for the estimation. Moreover, it is shown that several existing models are outperformed by the procedure developed in this paper.

Suggested Citation

  • Florian Ziel & Rick Steinert & Sven Husmann, 2014. "Efficient Modeling and Forecasting of the Electricity Spot Price," Papers 1402.7027, arXiv.org, revised Oct 2014.
    • Handle: RePEc:arx:papers:1402.7027
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1402.7027
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guthrie, Graeme & Videbeck, Steen, 2007. "Electricity spot price dynamics: Beyond financial models," Energy Policy, Elsevier, vol. 35(11), pages 5614-5621, November.
    2. Bowden, Nicholas & Payne, James E., 2008. "Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models," Energy Economics, Elsevier, vol. 30(6), pages 3186-3197, November.
    3. Knittel, Christopher R. & Roberts, Michael R., 2005. "An empirical examination of restructured electricity prices," Energy Economics, Elsevier, vol. 27(5), pages 791-817, September.
    4. Würzburg, Klaas & Labandeira, Xavier & Linares, Pedro, 2013. "Renewable generation and electricity prices: Taking stock and new evidence for Germany and Austria," Energy Economics, Elsevier, vol. 40(S1), pages 159-171.
    5. Keles, Dogan & Genoese, Massimo & Möst, Dominik & Ortlieb, Sebastian & Fichtner, Wolf, 2013. "A combined modeling approach for wind power feed-in and electricity spot prices," Energy Policy, Elsevier, vol. 59(C), pages 213-225.
    6. Hsu, Nan-Jung & Hung, Hung-Lin & Chang, Ya-Mei, 2008. "Subset selection for vector autoregressive processes using Lasso," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3645-3657, March.
    7. Kristiansen, Tarjei, 2012. "Forecasting Nord Pool day-ahead prices with an autoregressive model," Energy Policy, Elsevier, vol. 49(C), pages 328-332.
    8. Ren, Yunwen & Zhang, Xinsheng, 2010. "Subset selection for vector autoregressive processes via adaptive Lasso," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1705-1712, December.
    9. repec:qut:auncer:2012_5 is not listed on IDEAS
    10. Karakatsani, Nektaria V. & Bunn, Derek W., 2008. "Forecasting electricity prices: The impact of fundamentals and time-varying coefficients," International Journal of Forecasting, Elsevier, vol. 24(4), pages 764-785.
    11. Keles, Dogan & Genoese, Massimo & Möst, Dominik & Fichtner, Wolf, 2012. "Comparison of extended mean-reversion and time series models for electricity spot price simulation considering negative prices," Energy Economics, Elsevier, vol. 34(4), pages 1012-1032.
    12. Bordignon, Silvano & Bunn, Derek W. & Lisi, Francesco & Nan, Fany, 2013. "Combining day-ahead forecasts for British electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 88-103.
    13. Hansheng Wang & Guodong Li & Chih‐Ling Tsai, 2007. "Regression coefficient and autoregressive order shrinkage and selection via the lasso," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(1), pages 63-78, February.
    14. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
    15. Bruno Bosco & Lucia Parisio & Matteo Pelagatti, 2006. "Deregulated Wholesale Electricity Prices in Italy," Working Papers 20060301, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica, revised Apr 2006.
    16. Liebl, Dominik, 2013. "Modeling and Forecasting Electricity Spot Prices: A Functional Data Perspective," MPRA Paper 50881, University Library of Munich, Germany.
    17. Alvaro Escribano & J. Ignacio Peña & Pablo Villaplana, 2011. "Modelling Electricity Prices: International Evidence," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 73(5), pages 622-650, October.
    18. Liu, Heping & Shi, Jing, 2013. "Applying ARMA–GARCH approaches to forecasting short-term electricity prices," Energy Economics, Elsevier, vol. 37(C), pages 152-166.
    19. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo, 2008. "The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany," Energy Policy, Elsevier, vol. 36(8), pages 3076-3084, August.
    20. Koopman, Siem Jan & Ooms, Marius & Carnero, M. Angeles, 2007. "Periodic Seasonal Reg-ARFIMAGARCH Models for Daily Electricity Spot Prices," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 16-27, March.
    21. Mak, T. K. & Wong, H. & Li, W. K., 1997. "Estimation of nonlinear time series with conditional heteroscedastic variances by iteratively weighted least squares," Computational Statistics & Data Analysis, Elsevier, vol. 24(2), pages 169-178, April.
    22. Huisman, Ronald & Kilic, Mehtap, 2012. "Electricity Futures Prices: Indirect Storability, Expectations, and Risk Premiums," Energy Economics, Elsevier, vol. 34(4), pages 892-898.
    23. Bruno Bosco & Lucia Parisio & Matteo Pelagatti, 2007. "Deregulated Wholesale Electricity Prices in Italy: An Empirical Analysis," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 13(4), pages 415-432, November.
    24. Edenhofer, Ottmar & Hirth, Lion & Knopf, Brigitte & Pahle, Michael & Schlömer, Steffen & Schmid, Eva & Ueckerdt, Falko, 2013. "On the economics of renewable energy sources," Energy Economics, Elsevier, vol. 40(S1), pages 12-23.
    25. Christensen, T.M. & Hurn, A.S. & Lindsay, K.A., 2012. "Forecasting spikes in electricity prices," International Journal of Forecasting, Elsevier, vol. 28(2), pages 400-411.
    26. Woo, C.K. & Horowitz, I. & Moore, J. & Pacheco, A., 2011. "The impact of wind generation on the electricity spot-market price level and variance: The Texas experience," Energy Policy, Elsevier, vol. 39(7), pages 3939-3944, July.
    27. repec:kap:iaecre:v:13:y:2007:i:4:p:415-432 is not listed on IDEAS
    28. 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.
    29. Fanone, Enzo & Gamba, Andrea & Prokopczuk, Marcel, 2013. "The case of negative day-ahead electricity prices," Energy Economics, Elsevier, vol. 35(C), pages 22-34.
    30. Ronald Huisman & Victoria Stradnic & Sjur Westgaard, 2013. "Renewable energy and electricity prices: indirect empirical evidence from hydro power," Working Papers 2013/24, Institut d'Economia de Barcelona (IEB).
    31. Ronald Huisman & Victoria Stradnic & Sjur Westgaard, 2013. "Renewable energy and electricity prices: indirect empirical evidence from hydro power," Working Papers 2013/24, Institut d'Economia de Barcelona (IEB).
    32. Rafal Weron, 2006. "Modeling and Forecasting Electricity Loads and Prices: A Statistical Approach," HSC Books, Hugo Steinhaus Center, Wroclaw University of Technology, number hsbook0601.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ambach, Daniel & Croonenbroeck, Carsten, 2014. "Obtaining superior wind power predictions from a periodic and heteroscedastic Wind Power Prediction Tool," Discussion Papers 361, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.

    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. Ziel, Florian & Steinert, Rick & Husmann, Sven, 2015. "Efficient modeling and forecasting of electricity spot prices," Energy Economics, Elsevier, vol. 47(C), pages 98-111.
    2. Weron, Rafał, 2014. "Electricity price forecasting: A review of the state-of-the-art with a look into the future," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1030-1081.
    3. Ioannidis, Filippos & Kosmidou, Kyriaki & Savva, Christos & Theodossiou, Panayiotis, 2021. "Electricity pricing using a periodic GARCH model with conditional skewness and kurtosis components," Energy Economics, Elsevier, vol. 95(C).
    4. Kyritsis, Evangelos & Andersson, Jonas & Serletis, Apostolos, 2017. "Electricity prices, large-scale renewable integration, and policy implications," Energy Policy, Elsevier, vol. 101(C), pages 550-560.
    5. Ziel, Florian & Steinert, Rick, 2016. "Electricity price forecasting using sale and purchase curves: The X-Model," Energy Economics, Elsevier, vol. 59(C), pages 435-454.
    6. Florian Ziel & Rick Steinert, 2015. "Electricity Price Forecasting using Sale and Purchase Curves: The X-Model," Papers 1509.00372, arXiv.org, revised Aug 2016.
    7. Lisi, Francesco & Nan, Fany, 2014. "Component estimation for electricity prices: Procedures and comparisons," Energy Economics, Elsevier, vol. 44(C), pages 143-159.
    8. G P Girish & Aviral Kumar Tiwari, 2016. "A comparison of different univariate forecasting models forSpot Electricity Price in India," Economics Bulletin, AccessEcon, vol. 36(2), pages 1039-1057.
    9. Ziel, Florian & Steinert, Rick & Husmann, Sven, 2015. "Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets," Energy Economics, Elsevier, vol. 51(C), pages 430-444.
    10. Pape, Christian & Hagemann, Simon & Weber, Christoph, 2016. "Are fundamentals enough? Explaining price variations in the German day-ahead and intraday power market," Energy Economics, Elsevier, vol. 54(C), pages 376-387.
    11. repec:dui:wpaper:1502 is not listed on IDEAS
    12. Sirin, Selahattin Murat & Yilmaz, Berna N., 2021. "The impact of variable renewable energy technologies on electricity markets: An analysis of the Turkish balancing market," Energy Policy, Elsevier, vol. 151(C).
    13. Gianfreda, Angelica & Grossi, Luigi, 2012. "Forecasting Italian electricity zonal prices with exogenous variables," Energy Economics, Elsevier, vol. 34(6), pages 2228-2239.
    14. Nowotarski, Jakub & Tomczyk, Jakub & Weron, Rafał, 2013. "Robust estimation and forecasting of the long-term seasonal component of electricity spot prices," Energy Economics, Elsevier, vol. 39(C), pages 13-27.
    15. Thao Pham & Killian Lemoine, 2020. "Impacts of subsidized renewable electricity generation on spot market prices in Germany : Evidence from a GARCH model with panel data," Working Papers hal-02568268, HAL.
    16. Ergemen, Yunus Emre & Haldrup, Niels & Rodríguez-Caballero, Carlos Vladimir, 2016. "Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads," Energy Economics, Elsevier, vol. 60(C), pages 79-96.
    17. Angelica Gianfreda & Derek Bunn, 2018. "A Stochastic Latent Moment Model for Electricity Price Formation," BEMPS - Bozen Economics & Management Paper Series BEMPS46, Faculty of Economics and Management at the Free University of Bozen.
    18. Bartosz Uniejewski & Jakub Nowotarski & Rafał Weron, 2016. "Automated Variable Selection and Shrinkage for Day-Ahead Electricity Price Forecasting," Energies, MDPI, vol. 9(8), pages 1-22, August.
    19. S. Vijayalakshmi & G. P. Girish, 2015. "Artificial Neural Networks for Spot Electricity Price Forecasting: A Review," International Journal of Energy Economics and Policy, Econjournals, vol. 5(4), pages 1092-1097.
    20. François Benhmad & Jacques Percebois, 2016. "Wind power feed-in impact on electricity prices in Germany 2009-2013," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 81-96, June.
    21. Papaioannou, George P. & Dikaiakos, Christos & Dagoumas, Athanasios S. & Dramountanis, Anargyros & Papaioannou, Panagiotis G., 2018. "Detecting the impact of fundamentals and regulatory reforms on the Greek wholesale electricity market using a SARMAX/GARCH model," Energy, Elsevier, vol. 142(C), pages 1083-1103.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1402.7027. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.