Lebenslauf:

seit 02.2025 Professor für BWL, insb. Data Science in Energy and Environment, Universität Duisburg-Essen

08.2024-02.2025 Professor für Umweltökonomik, insb. Ökonomik erneuerbarer Energien, Universität Duisburg-Essen

03.2023-09.2023 Elternzeit (mit Teilzeitanstellung als Juniorprofessor)

07.2021-10.2021 Elternzeit (mit Teilzeitanstellung als Juniorprofessor)

07.2020-06.2025 Berufenes Mitglied der Jungen Akademie an der Berlin-Brandenburgischen Akademie der Wissenschaften (BBAW) und der Nationalen Akademie der Wissenschaften Leopoldina

02.2017-08.2024 Juniorprofessor für Umweltökonomik, insb. Ökonomik erneuerbarer Energien, Universität Duisburg-Essen

04.2019-09.2019 Elternzeit (mit Teilzeitanstellung als Juniorprofessor)

01.2019-04.2019 Forschungsaufenthalt im Programm 'The Mathematics for Energy Systems', Isaac Newton Institute, Cambridge,

09.2012-01.2017 Wissenschaftlicher Mitarbeiter, Fakultät für Wirtschaftswissenschaften, Europa-Universität Viadrina, Frankfurt (Oder)

07.2016-12.2016 Academic Visitor am Centre for Industrial and Applied Mathematics (OCIAM), University of Oxford, Oxford, UK

09.2012-06.2016 Promotion in Wirtschaftswissenschaften an der Europa-Universität Viadrina, Frankfurt (Oder)

06.2015-09.2015 DAAD-Forschungsaufenthalt am European Centre for Advanced Research in Economics and Statistics (ECARES) der Université libre de Bruxelles (ULB), Brüssel, Belgien

10.2008-02.2013 Diplom in Mathematik (Diplommathematiker), Technische Universität Dresden, Dresden

09.2011-08.2012 M.Sc. in Statistics, University College Dublin, Dublin, Ireland

10.2008-02.2013 Diplom Mathematik, Technische Universität Dresden, Dresden

09.2011-08.2012 M.Sc. in Statistics, University College Dublin, Dublin, Irland

Publikationen:

• Ghelasi, Paul; Ziel, Florian: From day-ahead to mid and long-term horizons with econometric electricity price forecasting models. In: Renewable and Sustainable Energy Reviews, Jg.217 (2025), S. 115684. doi:10.1016/j.rser.2025.115684DetailsVolltextBIB Download
• Zimmermann, Monika; Ziel, Florian: Efficient mid-term forecasting of hourly electricity load using generalized additive models. In: Applied Energy (2025). doi:10.1016/j.apenergy.2025.125444DetailsVolltextBIB Download
• Uniejewski, Bartosz; Ziel, Florian: Probabilistic Forecasts of Load, Solar and Wind for Electricity Price Forecasting. In: arXiv preprint arXiv:2501.06180 (2025). DetailsBIB Download
• Ghelasi, Paul; Ziel, Florian: A data-driven merit order: Learning a fundamental electricity price model. In: arXiv preprint arXiv:2501.02963 (2025). DetailsBIB Download
• Alvisi, S; Franchini, M; Marsili, V; Mazzoni, F; Salomons, E; Housh, M; Abokifa, A; Arsova, K; Ayyash, F; Bae, H; Others; Kley-Holsteg, Jens; Others; Sonnenschein, Björn; Others; Ziel, Florian; Zou, J.: Battle of Water Demand Forecasting. In: Journal of Water Resources Planning and Management, Jg.151 (2025), S. 4025049. DetailsBIB Download
• 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.2837DetailsVolltextBIB Download
• Ghelasi, Paul; Ziel, Florian: Far beyond day-ahead with econometric models for electricity price forecasting. In: arXiv preprint arXiv:2406.00326 (2024). DetailsBIB Download
• Alberizzi, Andrea; Di Barba, Paolo; Ziel, Florian: Agent based modeling for intraday electricity markets. In: OPSEARCH (2024), S. 1-20. DetailsBIB Download
• 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). DetailsBIB Download
• 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.2024.01.005KurzfassungDetailsVolltextBIB Download

  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; Berrisch, Jonathan; Ziel, Florian: Online distributional regression. In: arXiv preprint arXiv:2407.08750 (2024). DetailsBIB Download
• Zimmermann, Monika; Ziel, Florian: Spatial weather, socio-economic and political risks in probabilistic load forecasting. In: arXiv preprint arXiv:2408.00507 (2024). DetailsBIB Download
• Kley-Holsteg, Jens; Sonnenschein, Björn; Johnen, Gregor; Ziel, Florian: Water Demand Forecasting Based on Online Aggregation for District Meter Areas-Specific Adaption. In: Engineering Proceedings, Jg.69 (2024), S. 15. DetailsBIB Download
• Johnen, Gregor; Kley-Holsteg, Jens; Niemann, André; Ziel, Florian: Optimising Water Supply--Application of Probabilistic Deep Neural Networks to. In: AI in Business and Economics (2024), S. 243. DetailsBIB Download
• 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:10.1029/2022WR033826DetailsBIB Download
• Marcjasz, Grzegorz; Narajewski, Michał; Weron, Rafał; Ziel, Florian: Distributional neural networks for electricity price forecasting. In: Energy Economics (2023). doi:10.1016/j.eneco.2023.106843DetailsBIB Download
• Sgarlato, Raffaele; Ziel, Florian: The Role of Weather Predictions in Electricity Price Forecasting Beyond the Day-Ahead Horizon. In: IEEE Transactions on Power Systems, Jg.38 (2023), Nr. 3, S. 2500-2511. doi:10.1109/TPWRS.2022.3180119DetailsBIB Download
• 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.shirDetailsBIB Download
• Berrisch, Jonathan; Ziel, Florian: CRPS learning. In: Journal of Econometrics, Jg.237 (2023), S. 105221. doi:10.1016/j.jeconom.2021.11.008KurzfassungDetailsVolltextBIB Download

  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, Michał; Ziel, Florian: High-resolution peak demand estimation using generalized additive models and deep neural networks. In: Energy and AI, Jg.13 (2023), S. 100236. doi:10.1016/j.egyai.2023.100236DetailsVolltextBIB Download
• Berrisch, Jonathan; Pappert, Sven; Ziel, Florian; Arsova, Antonia: Modeling volatility and dependence of European carbon and energy prices. In: Finance Research Letters, Jg.52 (2023), S. 103503. doi:10.1016/j.frl.2022.103503DetailsVolltextBIB Download
• 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.2022.11.004DetailsBIB Download
• 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, Jg.301 (2022), Nr. 2, S. 726-746. DetailsBIB Download
• 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, Jg.110 (2022). doi:10.1016/j.eneco.2022.105974DetailsBIB Download
• 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, Jg.9 (2022), S. 202-212. DetailsBIB Download
• 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). DetailsBIB Download
• Ziel, Florian: M5 Competition Uncertainty: Overdispersion, distributional forecasting, GAMLSS and beyond.. In: International Journal of Forecasting (2021). doi:10.1016/j.ijforecast.2021.09.008DetailsBIB Download
• 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.4177DetailsBIB Download
• Rostami-Tabar, Bahman; Ziel, Florian: Anticipating special events in Emergency Department forecasting. In: International Journal of Forecasting (2021). doi:10.1016/j.ijforecast.2020.01.001DetailsVolltextBIB Download
• Narajewski, Michal; Kley-Holsteg, Jens; Ziel, Florian: tsrobprep – an R package for robust preprocessing of time series data.. In: SoftwareX, Jg.16 (2021). doi:10.1016/j.softx.2021.100809DetailsBIB Download
• Kath, Christopher; Ziel, Florian: Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets. In: International Journal of Forecasting, Jg.37 (2021), S. 777-799. doi:10.1016/j.ijforecast.2020.09.006DetailsVolltextBIB Download
• Furtwängler, Christian; Weber, Christoph; Ziel, Florian: Uncertainties in Energy and Electricity Markets: An Introduction. In: Economics of Energy & Environmental Policy (2021). DetailsBIB Download
• 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.skulDetailsVolltextBIB Download
• Ziel, Florian: The energy distance for ensemble and scenario reduction. In: Philosophical Transactions A, Jg.379 (2021), Nr. 2202. doi:10.1098/rsta.2019.0431DetailsVolltextBIB Download
• Narajewski, Michal; Ziel, Florian: Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories. In: Applied Energy (2020). doi:10.1016/j.apenergy.2020.115801DetailsVolltextBIB Download
• Kley-Holsteg, Jens; Ziel, Florian: Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso. In: Journal of Water Resources Planning and Management, Jg.146 (2020), Nr. 10. doi:10.1061/(ASCE)WR.1943-5452.0001268DetailsVolltextBIB Download
• Muniain, Peru; Ziel, Florian: Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices. In: International Journal of Forecasting, Jg.36 (2020), Nr. 4, S. 1193-1210. doi:10.1016/j.ijforecast.2019.11.006DetailsVolltextBIB Download
• Narajewski, Michal; Ziel, Florian: Changes in Electricity Demand Pattern in Europe Due to COVID-19 Shutdowns. In: IAEE Energy Forum (2020), S. 44-47. PDFDetailsVolltextBIB Download
• Ziel, Florian: Load Nowcasting: Predicting Actuals with Limited Data. In: Energies, Jg.13 (2020), Nr. 6. doi:10.3390/en13061443PDFDetailsVolltextBIB Download
• Narajewski, Michal; Ziel, Florian: Econometric modelling and forecasting of intraday electricity prices. In: Journal of Commodity Markets, Jg.19 (2020), Nr. 4. doi:10.1016/j.jcomm.2019.100107PDFDetailsVolltextBIB Download
• Narajewski, Michal; Ziel, Florian: Estimation and Simulation of the Transaction Arrival Process in Intraday Electricity Markets. In: Energies, Jg.12 (2019), Nr. 23. doi:10.3390/en12234518PDFDetailsVolltextBIB Download
• Kulakov, Sergei; Ziel, Florian: Determining fundamental supply and demand curves in a wholesale electricity market. In: arXiv preprint arXiv:1903.11383 (2019). DetailsVolltextBIB Download
• 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, Jg.35 (2019), S. 1469-1484. DetailsVolltextBIB Download
• Ziel, Florian; Berk, Kevin: Multivariate forecasting evaluation: On sensitive and strictly proper scoring rules. In: arXiv preprint arXiv:1910.07325 (2019). DetailsVolltextBIB Download
• Kath, Christopher; Ziel, Florian: The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts. In: Energy Economics, Jg.76 (2018), S. 411-423. doi:10.1016/j.eneco.2018.10.005DetailsVolltextBIB Download
• Ziel, Florian; Steinert, Rick: Probabilistic mid- and long-term electricity price forecasting. In: Renewable and Sustainable Energy Reviews, Jg.94 (2018), S. 251-266. doi:10.1016/j.rser.2018.05.038DetailsVolltextBIB Download
• Ziel, Florian: Quantile Regression for Qualifying Match of GEFCom2017 Probabilistic Load Forecasting. In: International Journal of Forecasting (2018). doi:10.1016/j.ijforecast.2018.07.004DetailsBIB Download
• 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.rsteDetailsBIB Download
• Ziel, Florian: Modeling public holidays in load forecasting: a German case study. In: Journal of Modern Power Systems and Clean Energy, Jg.6 (2018), Nr. 2, S. 191-207. DetailsVolltextBIB Download
• Ziel, Florian; Weron, Rafal: Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks. In: Energy Economics, Jg.70 (2018), S. 396-420. doi:10.1016/j.eneco.2017.12.016DetailsVolltextBIB Download
• Muniain, Peru; Ziel, Florian: Probabilistic forecasting and simulation of electricity prices. In: arXiv preprint arXiv:1810.08418 (2018). DetailsVolltextBIB Download
• Uniejewski, Bartosz; Weron, Rafal; Ziel, Florian: Variance Stabilizing Transformations for Electricity Spot Price Forecasting. In: IEEE Transactions on Power Systems, Jg.99 (2017), Nr. 1. doi:10.1109/TPWRS.2017.2734563DetailsVolltextBIB Download
• 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.2017.0626DetailsBIB Download
• 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.2017.7981900DetailsVolltextBIB Download
• Ziel, Florian: Forecasting Electricity Spot Prices Using Lasso: On Capturing the Autoregressive Intraday Structure. In: IEEE Transactions on Power Systems, Jg.31 (2016), Nr. 6, S. 4977-4987. doi:10.1109/TPWRS.2016.2521545DetailsVolltextBIB Download
• Ziel, Florian; Steinert, Rick: Electricity price forecasting using sale and purchase curves: The X-Model. In: Energy Economics, Jg.59 (2016), S. 435-454. doi:10.1016/j.eneco.2016.08.008DetailsVolltextBIB Download
• Ziel, Florian; Croonenbroeck, Carsten; Ambach, Daniel: Forecasting wind power - Modeling periodic and non-linear effects under conditional heteroscedasticity. In: Applied Energy, Jg.177 (2016), S. 285-297. doi:10.1016/j.apenergy.2016.05.111DetailsVolltextBIB Download
• Ziel, Florian: Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes. In: Computational Statistics & Data Analysis, Jg.100 (2016), S. 773-793. doi:10.1016/j.csda.2015.11.016DetailsVolltextBIB Download
• Ziel, Florian; Liu, Bidong: Lasso estimation for GEFCom2014 probabilistic electric load forecasting. In: International Journal of Forecasting, Jg.32 (2016), Nr. 3, S. 1029-1037. doi:10.1016/j.ijforecast.2016.01.001DetailsVolltextBIB Download
• Ziel, Florian: Modelling and forecasting electricity load using lasso methods. In: Modern Electric Power Systems (MEPS), 2015. IEEE, 2016, S. 1-6. doi:10.1109/MEPS.2015.7477217DetailsVolltextBIB Download
• 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, Jg.51 (2015), S. 430-444. doi:10.1016/j.eneco.2015.08.005DetailsVolltextBIB Download
• Ziel, Florian: Quasi-maximum Likelihood Estimation of Periodic Autoregressive, Conditionally Heteroscedastic Time Series. In: Steland, A.; Rafajłowicz, E.; Szajowski, K. (Hrsg.): Stochastic Models, Statistics and Their Applications. Springer Proceedings in Mathematics & Statistics. Springer, 2015, S. 207-214. doi:10.1007/978-3-319-13881-7_23DetailsVolltextBIB Download
• Ziel, Florian; Steinert, Rick; Husmann, Sven: Efficient modeling and forecasting of electricity spot prices. In: Energy Economics, Jg.47 (2015), S. 98-111. doi:10.1016/j.eneco.2014.10.012DetailsVolltextBIB Download

Vorträge:

• Ziel, Florian: Generating And Evaluating Probabilistic Forecasts - A Tutorial. ISF 2024, 01.07.2024, Dijon, France.
• Ziel, Florian: Electricity Price Forecasting. DLR Seminar, 08.05.2024, Virtual, Cottbus.
• Ziel, Florian: Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Price Forecasting. SMSA 2024, 12.03.2024, TU Delft.
• Ziel, Florian: Trading in hourly and quarter-hourly electricity price auctions. Economics Seminar, 10.01.2024, Essen.
• Ziel, Florian: Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Price Forecasting. Statistische Woche, 04.09.2023, Dortmund.
• Ziel, Florian: Electricity Price Forecasting: Data Science Meets Fundamental Models. 6th Energy Finance Italia, 08.02.2023, Milan, Italy.
• Ziel, Florian: Multivariate CRPS Learning. 42th International Symposium on Forecasting (ISF2022), 13.07.2022, Oxford, UK.
• Ziel, Florian: CRPS Learning. RuhrMetrics Seminar 2022, 24.06.2022, Bochum, Germany.
• Ziel, Florian: Optimal Probabilistic Forecast Combination Using CRPS Learning. International Conference on Computational Finance (ICCF) 2022, 06.06.2022, Wuppertal, Germany.
• Ziel, Florian: Data Science Models Meet Fundamental Models: Modern Electricity Price Forecasting Approaches . Fundamental and Stochastic Models in Energy Systems (digital), 01.05.2022, Karlsruhe/Cottbus, Germany.
• Ziel, Florian: CRPS Learning. Energy Finance Seminar, 18.04.2022, Stolberg(Harz), Germany.
• Ziel, Florian: Western Power Distribution Data Challenge on Estimating Electric Vehicle Charger Demand. WPD Challenge #2 - Winner Presentation (digital), 15.03.2022, Bristol, UK.
• Ziel, Florian: The Impact of Renewable Energy Forecasts on Intraday Electricity Prices. IAEE Webinar (digital), 01.03.2022, New York, US.
• Ziel, Florian: High Resolution Peak Demand Estimation Challenge. WPD Challenge #1 - Winner Presentation (digital), 21.01.2022, Bristol, UK.
• Ziel, Florian: Optimal bidding on hourly and quarter-hourly day-ahead electricity price auctions: trading large volumes of power with market impact and transaction costs. EPF Seminar 2021 - Virtual Seminar, 06.05.2021, Wroclaw, Poland.
• Ziel, Florian: Optimal online aggregation and bias reduction: Combining electricity price forecasts across calibration windows. 40th International Symposium on Forecasting (ISF2020) - Virtual Conference, 26.10.2020, Rio, Brasil.
• Ziel, Florian: Integrated day-ahead and intraday self-schedule bidding for energy storages using approximate dynamic programming. Digital GOR Workshop, 07.10.2020, Bochum, Germany.
• Ziel, Florian: Forecasting Combination in Energy Forecasting. Strommarkttreffen - Machine Learning, 10.04.2020, Berlin, Germany (canceled due to COVID19).
• Ziel, Florian: Electricity Load Nowcasting. Energy Finance Seminar, 01.04.2020, Stolberg(Harz), Germany (canceled due to COVID19).
• Ziel, Florian: Hybrid methods for short-term electricity price forecasting. Vattenfall - Workshop on short term price forecasting, 25.03.2020, Hamburg, Germany (canceled due to COVID19).
• Ziel, Florian: Integrated day-ahead and intraday self-schedule bidding for energy storages using approximate dynamic program- ming. GOR Workshop, 11.03.2020, Bochum, Germany (canceled due to COVID19).
• Ziel, Florian: Estimation and simulation of the transaction arrival process in intraday electricity markets. Energy Finance Christmas Workshop 2019, 12.12.2019, Dublin, Ireland.
• Ziel, Florian: Stochastic/Statistical Modelling of Electricity Prices. Hybrid Modelling of Energy Systems, 14.11.2019, Karlsruhe, Germany.
• Ziel, Florian: Combined Portfolio Rules under Parameter Uncertainty. Energy Finance Seminar, 18.04.2019, Stolberg(Harz), Germany.
• Ziel, Florian: Load and price forecasting. TenneT, 10.04.2019, Bayreuth, Germany.
• Ziel, Florian: Determining the Demand Elasticity in a Wholesale Electricity Market. Finance & Stochastics Research Seminar, 20.03.2019, University of Sussex, Brighton, UK.
• Ziel, Florian: Multivariate Forecasting Evaluation: On Sensitive and Strictly Proper Scoring Rules. Data and Analytics for Short-Term Operations, 14.02.2019, Cambridge, UK.
• Ziel, Florian: Determining the Demand Elasticity in a Wholesale Electricity Market. Energy Finance Christmas Workshop 2018, 12.12.2018, Bozen/Bolzano, Italy.
• Ziel, Florian: Probabilistic load forecasting. Strommarkttreffen, 24.08.2018, Berlin.
• Ziel, Florian: Marginal-Copula-Scores for Multivariate Forecasting Evaluation. Stochastisches Kolloquium, 21.06.2018, Siegen, Germany.
• Ziel, Florian: The impact of renewable energy forecasts on intra-day electricity prices. Strommarkttreffen, 01.06.2018, Berlin.
• Ziel, Florian: Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets. Computational Management Science (CMS 2018), 30.05.2018, Trondheim, Norway.
• Ziel, Florian: Modeling of the non-linear impact of renewable energy forecasts on intra-day electricity prices. Energy Finance Seminar, 18.04.2018, Stolberg (Harz).
• Ziel, Florian: Modeling of the non-linear impact of renewable energy forecasts on intra-day electricity prices. Workshop on forecasting for renewable energy production, 02.02.2018, EDF, Paris, France.
• Ziel, Florian: Prognosen in Energiemärkten. Euroforum, 09.01.2018, Düsseldorf.
• Ziel, Florian: Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures.. CMStatistics 2017: Stochastic modelling of energy markets, 16.12.2017, London, UK.
• Ziel, Florian: Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures.. Energy Finance Christmas Workshop 2017, 14.12.2017, Cracow, Poland.
• Ziel, Florian: The Energy Transition in Germany: What we can learn from the past for the future.. German-Arab Knowledge Transfer Colloquium on Water-Energy-Food Nexus: Energy Nexus, 28.11.2017, Duisburg.
• Ziel, Florian: Probabilistic Mid- and Long-Term Electricity Price Forecasting: A supply and demand curves based approach. 6th International Ruhr Energy Conference 2018 (INREC 2018), 01.09.2017, Essen.
• Ziel, Florian: Day-ahead electricity price forecasting with high-dimensional structures: Multi- vs. univariate modeling frameworks. ISF 2017, 37th International Symposium on Forecasting , 27.06.2017, Cairns, Australia.
• Ziel, Florian: Public Holidays in Energy Forecasting. ISAE, International Symposium on Energy Analytics, 22.06.2017, Cairns, Australia.
• Ziel, Florian: GEFCom2017. International Symposium on Energy Analytics, 22.06.2017, Cairns, Australia.
• Ziel, Florian: Electricity price forecasting using sale and purchase curves: The X-Model. IAEE 2017 40th Annual IAEE International Conference, 19.06.2017, Singapore.
• Ziel, Florian: Electricity Price Forecasting Using Supply and Demand Curves. Economics Colloquium, RUB, 14.06.2017, Bochum.
• Ziel, Florian: Modeling the impact of wind and solar power forecasting errors on intraday electricity prices. EEM2017 - 14 th International Conference on European Energy Market, 08.06.2017, Dresden.
• Ziel, Florian: Probabilistic Mid- and Long-Term Electricity Price Forecasting: A supply and demand curves based approach. Energy Finance Seminar, 19.04.2017, Stolberg (Harz).
• Ziel, Florian: Einführung in das Verständnis von Zeitreihen. Mathematik-Wettbewerb 12.Klasse, 30.03.2017, C.F.Gauß-Gymnasium Frankfurt(Oder).
• Ziel, Florian: Prognose von Strompreisen. IUTA, 23.03.2017, IUTA Duisburg.
• Ziel, Florian: On Proper Forecast Evaluation Based on the Energy Score and the Diebold-Mariano Test. S3-Seminar (Science meets Social Science), 16.03.2017, Wrolaw University of Technology.
• Ziel, Florian: Investigation of Short Term Load Forecasts of Low Voltage Level Substation Feeders and the Effects of Weather. 4th LV workshop: Demand analytics and control for networks support, 01.03.2017, Reading, UK.
• Ziel, Florian: Modelling and Forecasting of Electricity Load. 13th Workshop on Stochastic Models, Statistics and Their Applications, 24.02.2017, HU Berlin.
• Ziel, Florian: Electricity Price Forecasting using Sale and Purchase Curves: The X- Model. Strommarkttreffen - Thema: Strompreismodellierung, 10.02.2017, Innogy, Berlin.

Begleitete Abschlussarbeiten:

• Probabilistic Forecasting of European Electricity Prices (Masterarbeit Econometrics, 2025)
• Forecasting Electricity Price Using Distributional Neural Networks (Masterarbeit Econometrics, 2024)
• Analyzing Weather Effects in Short-Term Load Forecasting Using Feed-Forward Neural Networks (Bachelorarbeit Econometrics, 2024)
• Day-Ahead Electricity Price Forecasting Using GAMLSS (Masterarbeit Econometrics, 2024)
• Auswirkungen flexibler Stromtarife auf die Wirtschaftlichkeit von PV-Batteriesystemen (Bachelorarbeit Betriebswirtschaftslehre, 2024)
• Windkraftanlagentransport: Eine Kostenrechnungsperspektive (Bachelorarbeit Betriebswirtschaftslehre, 2024)
• Analyse der Kriterien beim Immobilienerwerb (Masterarbeit Märkte und Unternehmen, 2024)
• Dunkelflauten im Kontext der Energieversorgungssicherheit (Bachelorarbeit Betriebswirtschaftslehre, 2024)
• Nachhaltige Mobilität im Fokus: Evaluierung der Wirtschaftlichkeit von Elektro-Batterie- und Wasserstoffantrieben (Bachelorarbeit Betriebswirtschaftslehre, 2024)
• Vergleich ökologischer Aspekte von Nachhaltigkeitsberichten deutscher Automobilhersteller (Bachelorarbeit Betriebswirtschaftslehre, 2023)
• Analyse der Erdgasspeichersituation in Europa in 2022 (Bachelorarbeit Betriebswirtschaftslehre, 2023)
• Alternative Antriebssysteme – der direkte vergleich zwischen Elektro- und Wasserstoffautos (Bachelorarbeit Betriebswirtschaftslehre, 2023)
• Weltraumschrott: Problematik und Möglichkeiten zur Beseitung (Bachelorarbeit Betriebswirtschaftslehre, 2023)
• Nachhaltigkeit in Unternehmen – Eine Analyse am Beispiel des Nahrungsmittelkonzerns Nestlé (Bachelorarbeit Betriebswirtschaftslehre, 2023)
• Die Nutzung von Smart Metern in privaten Haushalten (Bachelorarbeit Betriebswirtschaftslehre, 2022)
• Kreislaufwirtschaft als Backstop-Technologie am Fallbeispiel Kunststoff (Bachelorarbeit Volkswirtschaftslehre, 2022)
• Herausforderung eines Wasserstoffmarktes (Bachelorarbeit Betriebswirtschaftslehre, 2022)
• Auswirkung von Treibhausemissionskosten auf den Produktionsstandort an einem Fallbeispiel (Bachelorarbeit Betriebswirtschaftslehre, 2022)
• Akzeptanz von Kernenergie in Europa (Bachelorarbeit Betriebswirtschaftslehre, 2022)
• Decision tree learning for modeling price auctions of day-ahead electricity markets (Masterarbeit BWL - Energy and Finance, 2021)
• Simulation-based Forecasting of Intraday Power Prices (Masterarbeit BWL - Energy and Finance, 2021)
• Intensive Landwirtschaft und deren Umweltauswirkungen im ökonomischen Kontext (Bachelorarbeit BWL - Energy and Finance, 2021)
• Welche Cryptocurrency ist hinsichtlich ihres Energieverbrauchs am effizientesten? (Bachelorarbeit BWL - Energy and Finance, 2021)
• Modelling the order book of the German (continuous) intraday electricity market (Masterarbeit BWL - Energy and Finance, 2020)
• Short-term renewables position management in intraday electricity markets (Masterarbeit BWL - Energy and Finance, 2020)
• Die CO₂-Steuer als Internalisierungsmaßnahme - eine theoretische Analyse (Bachelorarbeit Volkswirtschaftslehre, 2020)
• Data Science Methods for Probabilistic Natural Gas Price Forecasting (Masterarbeit BWL - Energy and Finance, 2020)
• Die Betrachtung erneuerbarer Energien nach Ende des EEG Förderzeitraumes - Eine betriebswirtschaftliche Sicht (Bachelorarbeit Betriebswirtschaftslehre, 2020)
• Der Vergleich von Vergleichsportalen - ein Vergleich von qualitativen und quantitativen Merkmalen (Bachelorarbeit Betriebswirtschaftslehre, 2020)
• Die Einführung neuer Sektoren in ein bestehendes Emissionshandelssystem (Bachelorarbeit BWL - Energy and Finance, 2020)
• Die Mehrkosten des Ökostroms - Ein Kostenvergleich zwischen grauem und grünem Strom (Bachelorarbeit Volkswirtschaftslehre, 2019)
• Autarke Stromversorgung von Insellösungen in Anlehnung an das Großprojekt "RedoxWind" (Bachelorarbeit BWL - Energy and Finance, 2019)
• The next trade - a continuous price model of the German intraday electricity market (Masterarbeit Betriebswirtschaftslehre, 2019)
• Statistical analysis of the probability of scenarios for the German electricity market (Masterarbeit BWL - Energy and Finance, 2019)
• Probabilistic Forecasting of Electrcity Prices using Derivative Data (Masterarbeit BWL - Energy and Finance, 2019)
• Econometrics of the German day-ahead control reserve market (Masterarbeit Econometrics, 2019)
• Wirtschaftlichkeitsvergleich eines Fuhrparks mit elektrischem und konventionellem Antrieb (Bachelorarbeit Betriebswirtschaftslehre, 2019)
• Kraftwerksbewertung im Hinblick auf CO₂-Emissionen (Bachelorarbeit BWL - Energy and Finance, 2019)
• Probabilistic Short-Term Water Demand Forecasting (Masterarbeit BWL - Energy and Finance, 2019)
• Ökonometriche Modellierung der Treibhausgasemissionen in Europa (Masterarbeit Econometrics, 2019)
• Verursachungsgerechte Abweichungsanalyse von Regressionsschätzungen als Analytisches Prüfungsverfahren (Masterarbeit BWL - Energy and Finance, 2019)
• Combination of wind power forecasts using data science methods (Masterarbeit Wirtschaftsinformatik, 2018)
• Investitionen in Photovoltaikanlagen im Rahmen des EEG 2017 (Bachelorarbeit, 2018)
• Ausschreibungen von onshore Windparks und deren Finanzierung (Bachelorarbeit BWL - Energy and Finance, 2018)