Publications
- Berrisch, Jonathan; Ziel, Florian: Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices. In: International Journal of Forecasting (2024). doi:10.1016/j.ijforecast.2024.01.005Full textCitationAbstractDetails
This paper presents a new method for combining (or aggregating or ensembling) multivariate probabilistic forecasts, considering dependencies between quantiles and marginals through a smoothing procedure that allows for online learning. We discuss two smoothing methods: dimensionality reduction using Basis matrices and penalized smoothing. The new online learning algorithm generalizes the standard CRPS learning framework into multivariate dimensions. It is based on Bernstein Online Aggregation (BOA) and yields optimal asymptotic learning properties. The procedure uses horizontal aggregation, i.e., aggregation across quantiles. We provide an in-depth discussion on possible extensions of the algorithm and several nested cases related to the existing literature on online forecast combination. We apply the proposed methodology to forecasting day-ahead electricity prices, which are 24-dimensional distributional forecasts. The proposed method yields significant improvements over uniform combination in terms of continuous ranked probability score (CRPS). We discuss the temporal evolution of the weights and hyperparameters and present the results of reduced versions of the preferred model. A fast C++implementation of the proposed algorithm is provided in the open-source R-Package profoc on CRAN.
- Hirsch, Simon; Ziel, Florian: Multivariate simulation-based forecasting for intraday power markets: Modeling cross-product price effects. In: Applied Stochastic Models in Business and Industry (2024). doi:10.1002/asmb.2837Full textCitationDetails
- Zimmermann, Monika; Ziel, Florian: Efficient mid-term forecasting of hourly electricity load using generalized additive models. In: arXiv preprint arXiv:2405.17070 (2024). CitationDetails
- Ghelasi, Paul; Ziel, Florian: Far beyond day-ahead with econometric models for electricity price forecasting. In: arXiv preprint arXiv:2406.00326 (2024). CitationDetails
- Alberizzi, Andrea; Di Barba, Paolo; Ziel, Florian: Agent based modeling for intraday electricity markets. In: OPSEARCH (2024), p. 1-20. CitationDetails
- Peper, Jan; Kröger, David; Kipp, Jonathan; Ziel, Florian; Rehtanz, Christian: Assessing the impact of weather-induced uncertainties in large-scale electricity systems. In: arXiv preprint arXiv:2405.19845 (2024). CitationDetails
- Sonnenschein, Björn; Ziel, Florian: Probabilistic Intraday Wastewater Treatment Plant Inflow Forecast Utilizing Rain Forecast Data and Sewer Network Sensor Data. In: Water Resources Research (2023). doi:10.1029/2022WR033826CitationDetails
- Marcjasz, Grzegorz; Narajewski, Michał; Weron, Rafał; Ziel, Florian: Distributional neural networks for electricity price forecasting. In: Energy Economics (2023). doi:10.1016/j.eneco.2023.106843CitationDetails
- Sgarlato, Raffaele; Ziel, Florian: The Role of Weather Predictions in Electricity Price Forecasting Beyond the Day-Ahead Horizon. In: IEEE Transactions on Power Systems, Vol 38 (2023) No 3, p. 2500-2511. doi:10.1109/TPWRS.2022.3180119CitationDetails
- Hirsch, Simon; Ziel, Florian: Simulation-based Forecasting for Intraday Power Markets: Modelling Fundamental Drivers for Location, Shape and Scale of the Price Distribution. In: The Energy Journal (2023). doi:10.5547/01956574.45.3.shirCitationDetails
- Berrisch, Jonathan; Ziel, Florian: CRPS learning. In: Journal of Econometrics, Vol 237 (2023), p. 105221. doi:10.1016/j.jeconom.2021.11.008Full textCitationAbstractDetails
Combination and aggregation techniques can significantly improve forecast accuracy. This also holds for probabilistic forecasting methods where predictive distributions are combined. There are several time-varying and adaptive weighting schemes such as Bayesian model averaging (BMA). However, the quality of different forecasts may vary not only over time but also within the distribution. For example, some distribution forecasts may be more accurate in the center of the distributions, while others are better at predicting the tails. Therefore, we introduce a new weighting method that considers the differences in performance over time and within the distribution. We discuss pointwise combination algorithms based on aggregation across quantiles that optimize with respect to the continuous ranked probability score (CRPS). After analyzing the theoretical properties of pointwise CRPS learning, we discuss B- and P-Spline-based estimation techniques for batch and online learning, based on quantile regression and prediction with expert advice. We prove that the proposed fully adaptive Bernstein online aggregation (BOA) method for pointwise CRPS online learning has optimal convergence properties. They are confirmed in simulations and a probabilistic forecasting study for European emission allowance (EUA) prices.
- Berrisch, Jonathan; Narajewski, Michal; Ziel, Florian: High-resolution peak demand estimation using generalized additive models and deep neural networks. In: Energy and AI, Vol 13 (2023), p. 100236. Full textCitationDetails
- Berrisch, Jonathan; Pappert, Sven; Ziel, Florian; Arsova, Antonia: Modeling volatility and dependence of European carbon and energy prices. In: Finance Research Letters, Vol 52 (2023), p. 103503. doi:10.1016/j.frl.2022.103503Full textCitationDetails
- Ghelasi, Paul; Ziel, Florian: Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions. In: International Journal of Forecasting (2022). doi:10.1016/j.ijforecast.2022.11.004CitationDetails
- Finnah, Benedikt; Gönsch, Jochen; Ziel, Florian: Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming. In: European Journal of Operations Research, Vol 301 (2022) No 2, p. 726-746. CitationDetails
- Narajewski, Michal: Probabilistic Forecasting of German Electricity Imbalance Prices. In: Energies, Vol 15 (2022) No 14. doi:10.3390/en15144976CitationDetails
- Narajewski, Michal; Ziel, Florian: Optimal bidding in hourly and quarter-hourly electricity price auctions: Trading large volumes of power with market impact and transaction costs. In: Energy Economics, Vol 110 (2022). doi:10.1016/j.eneco.2022.105974CitationDetails
- Berrisch, Jonathan; Ziel, Florian: Distributional modeling and forecasting of natural gas prices. In: Journal of Forecasting, Vol 41 (2022), p. 1065-1086. doi:10.1002/for.2853Full textCitationDetails
- Ziel, Florian: Smoothed bernstein online aggregation for short-term load forecasting in ieee dataport competition on day-ahead electricity demand forecasting: Post-covid paradigm. In: IEEE Open Access Journal of Power and Energy, Vol 9 (2022), p. 202-212. CitationDetails
- Petropoulos, Fotios; Apiletti, Daniele; Assimakopoulos, Vassilios; Babai, Mohamed Zied; Barrow, Devon K.; Taieb, Souhaib Ben; Bergmeir, Christoph; . . .; Winkler, Robert L.; Yusupova, Alisa; Ziel, Florian: Forecasting: theory and practice. In: International Journal of Forecasting (2021). CitationDetails
- Ziel, Florian: M5 Competition Uncertainty: Overdispersion, distributional forecasting, GAMLSS and beyond.. In: International Journal of Forecasting (2021). doi:10.1016/j.ijforecast.2021.09.008CitationDetails
- Gonzalez, Paula; Brayshaw, David; Ziel, Florian: A new approach to subseasonal multi-model forecasting: Online prediction with expert advice.. In: Quarterly Journal of the Royal Meteorological Society (2021). doi:10.1002/qj.4177CitationDetails
- Rostami-Tabar, Bahman; Ziel, Florian: Anticipating special events in Emergency Department forecasting. In: International Journal of Forecasting (2021). doi:10.1016/j.ijforecast.2020.01.001Full textCitationDetails
- Narajewski, Michal; Kley-Holsteg, Jens; Ziel, Florian: tsrobprep – an R package for robust preprocessing of time series data.. In: SoftwareX, Vol 16 (2021). doi:10.1016/j.softx.2021.100809CitationDetails
- Kath, Christopher; Ziel, Florian: Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets. In: International Journal of Forecasting, Vol 37 (2021), p. 777-799. doi:10.1016/j.ijforecast.2020.09.006Full textCitationDetails
- Furtwängler, Christian; Weber, Christoph; Ziel, Florian: Uncertainties in Energy and Electricity Markets: An Introduction. In: Economics of Energy & Environmental Policy (2021). CitationDetails
- Kulakov, Sergei; Ziel, Florian: The impact of renewable energy forecasts on intraday electricity prices. In: Economics of Energy & Environmental Policy (2021). doi:10.5547/2160-5890.10.1.skulFull textCitationDetails
- Ziel, Florian: The energy distance for ensemble and scenario reduction. In: Philosophical Transactions A, Vol 379 (2021) No 2202. doi:10.1098/rsta.2019.0431Full textCitationDetails
- Narajewski, Michal; Ziel, Florian: Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories. In: Applied Energy (2020). doi:10.1016/j.apenergy.2020.115801Full textCitationDetails
- Kley-Holsteg, Jens; Ziel, Florian: Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso. In: Journal of Water Resources Planning and Management, Vol 146 (2020) No 10. doi:10.1061/(ASCE)WR.1943-5452.0001268Full textCitationDetails
- Muniain, Peru; Ziel, Florian: Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices. In: International Journal of Forecasting, Vol 36 (2020) No 4, p. 1193-1210. doi:10.1016/j.ijforecast.2019.11.006Full textCitationDetails
- Narajewski, Michal; Ziel, Florian: Changes in Electricity Demand Pattern in Europe Due to COVID-19 Shutdowns. In: IAEE Energy Forum (2020), p. 44-47. PDFFull textCitationDetails
- Ziel, Florian: Load Nowcasting: Predicting Actuals with Limited Data. In: Energies, Vol 13 (2020) No 6. doi:10.3390/en13061443PDFFull textCitationDetails
- Narajewski, Michal; Ziel, Florian: Econometric modelling and forecasting of intraday electricity prices. In: Journal of Commodity Markets, Vol 19 (2020) No 4. doi:10.1016/j.jcomm.2019.100107PDFFull textCitationDetails
- Kulakov, Sergei: X-model: further development and possible modifications. In: Forecasting, Vol 2 (2020), p. 20-35. CitationDetails
- Narajewski, Michal; Ziel, Florian: Estimation and Simulation of the Transaction Arrival Process in Intraday Electricity Markets. In: Energies, Vol 12 (2019) No 23. doi:10.3390/en12234518PDFFull textCitationDetails
- Kulakov, Sergei; Ziel, Florian: Determining fundamental supply and demand curves in a wholesale electricity market. In: arXiv preprint arXiv:1903.11383 (2019). Full textCitationDetails
- Haben, Stephen; Giasemidis, Georgios; Ziel, Florian; Arora, Siddharth: Short term load forecasting and the effect of temperature at the low voltage level. In: International Journal of Forecasting, Vol 35 (2019), p. 1469-1484. Full textCitationDetails
- Ziel, Florian; Berk, Kevin: Multivariate forecasting evaluation: On sensitive and strictly proper scoring rules. In: arXiv preprint arXiv:1910.07325 (2019). Full textCitationDetails
- Kath, Christopher: Modeling intraday markets under the new advances of the cross-border intraday project (XBID): Evidence from the German intraday market. In: Energies, Vol 12 (2019), p. 4339. CitationDetails
- Kath, Christopher; Ziel, Florian: The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts. In: Energy Economics, Vol 76 (2018), p. 411-423. doi:10.1016/j.eneco.2018.10.005Full textCitationDetails
- Ziel, Florian; Steinert, Rick: Probabilistic mid- and long-term electricity price forecasting. In: Renewable and Sustainable Energy Reviews, Vol 94 (2018), p. 251-266. doi:10.1016/j.rser.2018.05.038Full textCitationDetails
- Ziel, Florian: Quantile Regression for Qualifying Match of GEFCom2017 Probabilistic Load Forecasting. In: International Journal of Forecasting (2018). doi:10.1016/j.ijforecast.2018.07.004CitationDetails
- Steinert, Rick; Ziel, Florian: Short-to Mid-term Day-Ahead Electricity Price Forecasting Using Futures. In: The Energy Journal (2018). doi:10.5547/01956574.40.1.rsteCitationDetails
- Ziel, Florian: Modeling public holidays in load forecasting: a German case study. In: Journal of Modern Power Systems and Clean Energy, Vol 6 (2018) No 2, p. 191-207. Full textCitationDetails
- Ziel, Florian; Weron, Rafal: Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks. In: Energy Economics, Vol 70 (2018), p. 396-420. doi:10.1016/j.eneco.2017.12.016Full textCitationDetails
- Muniain, Peru; Ziel, Florian: Probabilistic forecasting and simulation of electricity prices. In: arXiv preprint arXiv:1810.08418 (2018). Full textCitationDetails
- Uniejewski, Bartosz; Weron, Rafal; Ziel, Florian: Variance Stabilizing Transformations for Electricity Spot Price Forecasting. In: IEEE Transactions on Power Systems, Vol 99 (2017) No 1. doi:10.1109/TPWRS.2017.2734563Full textCitationDetails
- Yunusov, Timur; Haben, Stephen; Lee, Tamsin; Ziel, Florian; Holderbaum, William; Potter, Ben: Evaluating the effectiveness of storage control in reducing peak demand on low voltage feeders. In: 24th International Conference & Exhibition on Electricity Distribution (CIRED). IET, 2017. doi:10.1049/oap-cired.2017.0626CitationDetails
- Ziel, Florian: Modeling the impact of wind and solar power forecasting errors on intraday electricity prices. In: 14th International Conference on the European Energy Market (EEM 2017). IEEE, 2017. doi:10.1109/EEM.2017.7981900Full textCitationDetails
- Ziel, Florian: Forecasting Electricity Spot Prices Using Lasso: On Capturing the Autoregressive Intraday Structure. In: IEEE Transactions on Power Systems, Vol 31 (2016) No 6, p. 4977-4987. doi:10.1109/TPWRS.2016.2521545Full textCitationDetails
- Ziel, Florian; Croonenbroeck, Carsten; Ambach, Daniel: Forecasting wind power - Modeling periodic and non-linear effects under conditional heteroscedasticity. In: Applied Energy, Vol 177 (2016), p. 285-297. doi:10.1016/j.apenergy.2016.05.111Full textCitationDetails
- Ziel, Florian; Steinert, Rick: Electricity price forecasting using sale and purchase curves: The X-Model. In: Energy Economics, Vol 59 (2016), p. 435-454. doi:10.1016/j.eneco.2016.08.008Full textCitationDetails
- Ziel, Florian: Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes. In: Computational Statistics & Data Analysis, Vol 100 (2016), p. 773-793. doi:10.1016/j.csda.2015.11.016Full textCitationDetails
- Ziel, Florian; Liu, Bidong: Lasso estimation for GEFCom2014 probabilistic electric load forecasting. In: International Journal of Forecasting, Vol 32 (2016) No 3, p. 1029-1037. doi:10.1016/j.ijforecast.2016.01.001Full textCitationDetails
- Ziel, Florian: Modelling and forecasting electricity load using lasso methods. In: Modern Electric Power Systems (MEPS), 2015. IEEE, 2016, p. 1-6. doi:10.1109/MEPS.2015.7477217Full textCitationDetails
- Ziel, Florian; Steinert, Rick; Husmann, Sven: Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets. In: Energy Economics, Vol 51 (2015), p. 430-444. doi:10.1016/j.eneco.2015.08.005Full textCitationDetails
- Ziel, Florian: Quasi-maximum Likelihood Estimation of Periodic Autoregressive, Conditionally Heteroscedastic Time Series. In: Steland, A.; Rafajłowicz, E.; Szajowski, K. (Ed.): Stochastic Models, Statistics and Their Applications. Springer Proceedings in Mathematics & Statistics. Springer, 2015, p. 207-214. doi:10.1007/978-3-319-13881-7_23Full textCitationDetails
- Ziel, Florian; Steinert, Rick; Husmann, Sven: Efficient modeling and forecasting of electricity spot prices. In: Energy Economics, Vol 47 (2015), p. 98-111. doi:10.1016/j.eneco.2014.10.012Full textCitationDetails
Software
CombinePortfolio R-package maintainer