Probabilistic forecasting of electricity prices and demand for risk management purposes
Grant no.: NCN 2015/17/B/HS4/00334
Funding agency: National Science Centre (NCN), Poland
Funding scheme: OPUS
Funding period: 15.02.2016-14.02.2019 (36 months)
Budget: 398 400 PLN
Title in Polish: Probabilistyczne prognozowanie cen i zapotrzebowania na energię elektryczną na potrzeby zarządzania ryzykiem
Principal Investigator (Kierownik):
- Tao Hong (UNCC, Charlotte, USA)
- Katarzyna Maciejowska (PWr, Wrocław, PL)
- Paweł Maryniak (UE, Wrocław, PL)
- Jakub Nowotarski (BNY Mellon, Wrocław, PL)
- Stefan Trück (MQ, Sydney, AUS)
- Florian Ziel (U.Duisburg-Essen, D)
– Ph.D. / M.Sc. / B.Sc. student
Aims and scope:
In a recent review article published in the International Journal of Forecasting, Weron (2014) identifies five challenges outstanding in the area of electricity price forecasting. The main objective of the project is to adequately address three of them:
- the importance of considering fundamental price drivers and of an appropriate choice of the input variables in electricity spot (or forward) price models,
- the need for developing techniques for probabilistic (i.e. interval or density) forecasting of electricity prices and demand, both for power exchange bidding and risk management purposes,
- the need for a universal test ground involving the same datasets and the same robust error evaluation procedures.
The project will be carried out within three tasks, which are interesting both from a basic research (development and validation of econometric techniques) and a utilitarian point of view (improving portfolio management and risk management practices in the energy sector).
- Development of robust variance stabilizing transformations and seasonal decomposition techniques for preprocessing electricity prices and demand.
- Development of new techniques for probabilistic forecasting of electricity prices and demand, in particular using sister models and expert forecasts.
- Development and validation of error measures for probabilistic forecasts tailored for the extremely volatile and seasonal electricity spot prices.
Peer-reviewed articles in JCR-listed journals
2018 (5+), 2017 (0), 2016 (3)
- G. Marcjasz, B. Uniejewski, R. Weron (2018) On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks, International Journal of Forecasting (https://doi.org/10.1016/j.ijforecast.2017.11.009). Earlier working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1703.html
- J. Nowotarski, R. Weron (2018) Recent advances in electricity price forecasting: A review of probabilistic forecasting, Renewable and Sustainable Energy Reviews 81(1), 1548-1568 (doi: 10.1016/j.rser.2017.05.234). Earlier working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1607.html
- B. Uniejewski, G. Marcjasz, R. Weron (2018) On the importance of the long-term seasonal component in day-ahead electricity price forecasting. Part II – Probabilistic forecasting, Energy Economics (doi: 10.1016/j.eneco.2018.02.007). Working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1702.html
- B. Uniejewski, R. Weron, F. Ziel (2018) Variance stabilizing transformations for electricity spot price forecasting, IEEE Transactions on Power Systems 33(2), 2219-2229 (doi: 10.1109/TPWRS.2017.2734563). Earlier working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1701.html
- F. Ziel, R. Weron (2018) Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks, Energy Economics 70, 396-420 (doi: 10.1016/j.eneco.2017.12.016). Earlier working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1608.html
- J. Nowotarski, R. Weron (2016) On the importance of the long-term seasonal component in day-ahead electricity price forecasting, Energy Economics 57, 228-235 (doi: 10.1016/j.eneco.2016.05.009). Working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1605.html. Matlab codes and data available from RePEc: https://ideas.repec.org/c/wuu/hscode/z16002.html
- S. Trück, R. Weron (2016) Convenience yields and risk premiums in the EU-ETS – Evidence from the Kyoto commitment period, Journal of Futures Markets 36(6), 587-611 (doi: 10.1002/fut.21780). Earlier working paper version available from RePEc: http://ideas.repec.org/p/wuu/wpaper/hsc1503.html
- B. Uniejewski, J. Nowotarski, R. Weron (2016) Automated variable selection and shrinkage for day-ahead electricity price forecasting, Energies 9(8), 621 (doi: 10.3390/en9080621). Working paper version available from RePEc: http://ideas.repec.org/p/wuu/wpaper/hsc1606.html
Peer-reviewed articles in non JCR-listed journals
- J. Nowotarski, R. Weron (2016) To combine or not to combine? Recent trends in electricity price forecasting, ARGO 9, 7-14. Available from ARGO Website. Working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1601.html
Forthcoming publications, submitted papers and work in progress
- P. Maryniak, R. Weron (2018) What is the probability of an electricity price spike? Evidence from the UK power market, in “Handbook of Energy Finance: Theories, Practices and Simulations”, eds. S. Goutte, D.K. Nguyen, World Scientific, forthcoming. Earlier working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1411.html
- P. Maryniak, S. Trück, R. Weron (2017) Carbon premiums and pass-through rates in Australian electricity futures markets, submitted. Working paper version available from RePEc: https://ideas.repec.org/p/wuu/wpaper/hsc1610.html