Curriculum Vitae:

since 02.2025 Professor (full) for Business Administration, esp. Data Science in Energy and Environment, University of Duisburg-Essen, Germany

08.2024-02.2025 Professor (full) for Environmental Economics, esp. Economics for Renewable Energies, University of Duisburg-Essen, Germany

03.2023-09.2023 Parental leave (with part time employment as Assistant Professor)

07.2021-10.2021 Parental leave (with part time employment as Assistant Professor)

07.2020-06.2025 Appointed Member of the Junge Akademie at the Berlin-Brandenburg Academy of Sciences and Humanities (BBAW) and the German National Academy of Sciences Leopoldina

02.2017-08.2024 Assistant Professor for Environmental Economics, esp. Economics for Renewable Energies, University of Duisburg-Essen, Germany

04.2019-09.2019 Parental leave (with part time employment as Assistant Professor)

01.2019-04.2019 Visiting researcher in the research programm 'The Mathematics for Energy Systems', Isaac Newton Institute, Cambridge, UK

09.2012-01.2017 Research Associate, Faculty of Business Administration and Economics, European University Viadrina, Frankfurt (Oder), Germany

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

09.2012-06.2016 PhD in Business Administration and Economics at the European University Viadrina, Frankfurt (Oder), Germany

06.2015-09.2015 DAAD-visiting research at the European Centre for Advanced Research in Economics and Statistics (ECARES) of the Université libre de Bruxelles (ULB), Brussels, Belgium

10.2008-02.2013 Diplom in Mathematics, Technical University of Dresden, Dresden, Germany

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

Publications:

• Ghelasi, Paul; Ziel, Florian: A data-driven merit order: Learning a fundamental electricity price model. In: Energy Economics, Vol154 (2026), p. 109114. doi:10.1016/j.eneco.2025.109114Abstract Details Full textCitation

  Electricity price forecasting approaches generally fall into two categories: data-driven models, which learn from historical patterns, or fundamental models, which simulate market mechanisms. We propose a novel and highly efficient data-driven merit order model that integrates both paradigms. The resulting supply stack framework embeds the classical expert-based merit order as a nested special case, allowing all key parameters, such as plant efficiencies, bidding behavior, and available capacities, to be estimated directly from historical data, rather than assumed. We further enhance the model with critical embedded extensions such as hydro power, cross-border flows and corrections for underreported capacities, which considerably improve forecasting accuracy. Applied to the German day-ahead market, our model outperforms both classic fundamental and state-of-the-art machine learning models. It retains the interpretability of fundamental models, offering insights into marginal technologies, fuel switches, and dispatch patterns, elements which are typically inaccessible to black-box machine learning approaches. This transparency and high computational efficiency make it a promising new direction for electricity price modeling.

• 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, Vol217 (2025), p. 115684. doi:10.1016/j.rser.2025.115684 Details Full textCitation
• 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.2025.125444 Details Full textCitation
• Uniejewski, Bartosz; Ziel, Florian: Probabilistic Forecasts of Load, Solar and Wind for Electricity Price Forecasting. In: arXiv preprint arXiv:2501.06180 (2025). Details Citation
• 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, Vol151 (2025), p. 4025049. Details Citation
• Ghelasi, Paul; Ziel, Florian: Far beyond day-ahead with econometric models for electricity price forecasting. In: arXiv preprint arXiv:2406.00326 (2024). Details Citation
• Alberizzi, Andrea; Di Barba, Paolo; Ziel, Florian: Agent based modeling for intraday electricity markets. In: OPSEARCH (2024), p. 1-20. Details Citation
• 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). Details Citation
• Hirsch, Simon; Berrisch, Jonathan; Ziel, Florian: Online distributional regression. In: arXiv preprint arXiv:2407.08750 (2024). Details Citation
• Zimmermann, Monika; Ziel, Florian: Spatial weather, socio-economic and political risks in probabilistic load forecasting. In: arXiv preprint arXiv:2408.00507 (2024). Details Citation
• 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.2024.01.005Abstract Details Full textCitation

  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.

• 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), p. 243. Details Citation
• 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.2837 Details Full textCitation
• 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, Vol69 (2024), p. 15. Details Citation
• 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:10.1029/2022WR033826 Details Citation
• Marcjasz, Grzegorz; Narajewski, Michał; Weron, Rafał; Ziel, Florian: Distributional neural networks for electricity price forecasting. In: Energy Economics (2023). doi:10.1016/j.eneco.2023.106843 Details Citation
• Sgarlato, Raffaele; Ziel, Florian: The Role of Weather Predictions in Electricity Price Forecasting Beyond the Day-Ahead Horizon. In: IEEE Transactions on Power Systems, Vol38 (2023), No 3, p. 2500-2511. doi:10.1109/TPWRS.2022.3180119 Details Citation
• 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.shir Details Citation
• Berrisch, Jonathan; Ziel, Florian: CRPS learning. In: Journal of Econometrics, Vol237 (2023), p. 105221. doi:10.1016/j.jeconom.2021.11.008Abstract Details Full textCitation

  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, Vol13 (2023), p. 100236. doi:10.1016/j.egyai.2023.100236 Details Full textCitation
• Berrisch, Jonathan; Pappert, Sven; Ziel, Florian; Arsova, Antonia: Modeling volatility and dependence of European carbon and energy prices. In: Finance Research Letters, Vol52 (2023), p. 103503. doi:10.1016/j.frl.2022.103503 Details Full textCitation
• 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.2022.11.004 Details Citation
• 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, Vol301 (2022), No 2, p. 726-746. Details Citation
• 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, Vol110 (2022). doi:10.1016/j.eneco.2022.105974 Details Citation
• 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, Vol9 (2022), p. 202-212. Details Citation
• 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). Details Citation
• Ziel, Florian: M5 Competition Uncertainty: Overdispersion, distributional forecasting, GAMLSS and beyond.. In: International Journal of Forecasting (2021). doi:10.1016/j.ijforecast.2021.09.008 Details Citation
• 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.4177 Details Citation
• Rostami-Tabar, Bahman; Ziel, Florian: Anticipating special events in Emergency Department forecasting. In: International Journal of Forecasting (2021). doi:10.1016/j.ijforecast.2020.01.001 Details Full textCitation
• Narajewski, Michal; Kley-Holsteg, Jens; Ziel, Florian: tsrobprep – an R package for robust preprocessing of time series data.. In: SoftwareX, Vol16 (2021). doi:10.1016/j.softx.2021.100809 Details Citation
• Kath, Christopher; Ziel, Florian: Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets. In: International Journal of Forecasting, Vol37 (2021), p. 777-799. doi:10.1016/j.ijforecast.2020.09.006 Details Full textCitation
• Furtwängler, Christian; Weber, Christoph; Ziel, Florian: Uncertainties in Energy and Electricity Markets: An Introduction. In: Economics of Energy & Environmental Policy (2021). Details Citation
• 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.skul Details Full textCitation
• Ziel, Florian: The energy distance for ensemble and scenario reduction. In: Philosophical Transactions A, Vol379 (2021), No 2202. doi:10.1098/rsta.2019.0431 Details Full textCitation
• Narajewski, Michal; Ziel, Florian: Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories. In: Applied Energy (2020). doi:10.1016/j.apenergy.2020.115801 Details Full textCitation
• Kley-Holsteg, Jens; Ziel, Florian: Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso. In: Journal of Water Resources Planning and Management, Vol146 (2020), No 10. doi:10.1061/(ASCE)WR.1943-5452.0001268 Details Full textCitation
• Muniain, Peru; Ziel, Florian: Probabilistic forecasting in day-ahead electricity markets: Simulating peak and off-peak prices. In: International Journal of Forecasting, Vol36 (2020), No 4, p. 1193-1210. doi:10.1016/j.ijforecast.2019.11.006 Details Full textCitation
• Narajewski, Michal; Ziel, Florian: Changes in Electricity Demand Pattern in Europe Due to COVID-19 Shutdowns. In: IAEE Energy Forum (2020), p. 44-47. PDF Details Full textCitation
• Ziel, Florian: Load Nowcasting: Predicting Actuals with Limited Data. In: Energies, Vol13 (2020), No 6. doi:10.3390/en13061443PDF Details Full textCitation
• Narajewski, Michal; Ziel, Florian: Econometric modelling and forecasting of intraday electricity prices. In: Journal of Commodity Markets, Vol19 (2020), No 4. doi:10.1016/j.jcomm.2019.100107PDF Details Full textCitation
• Narajewski, Michal; Ziel, Florian: Estimation and Simulation of the Transaction Arrival Process in Intraday Electricity Markets. In: Energies, Vol12 (2019), No 23. doi:10.3390/en12234518PDF Details Full textCitation
• Kulakov, Sergei; Ziel, Florian: Determining fundamental supply and demand curves in a wholesale electricity market. In: arXiv preprint arXiv:1903.11383 (2019). Details Full textCitation
• 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, Vol35 (2019), p. 1469-1484. Details Full textCitation
• Ziel, Florian; Berk, Kevin: Multivariate forecasting evaluation: On sensitive and strictly proper scoring rules. In: arXiv preprint arXiv:1910.07325 (2019). Details Full textCitation
• Kath, Christopher; Ziel, Florian: The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts. In: Energy Economics, Vol76 (2018), p. 411-423. doi:10.1016/j.eneco.2018.10.005 Details Full textCitation
• Ziel, Florian; Steinert, Rick: Probabilistic mid- and long-term electricity price forecasting. In: Renewable and Sustainable Energy Reviews, Vol94 (2018), p. 251-266. doi:10.1016/j.rser.2018.05.038 Details Full textCitation
• Ziel, Florian: Quantile Regression for Qualifying Match of GEFCom2017 Probabilistic Load Forecasting. In: International Journal of Forecasting (2018). doi:10.1016/j.ijforecast.2018.07.004 Details Citation
• 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.rste Details Citation
• Ziel, Florian: Modeling public holidays in load forecasting: a German case study. In: Journal of Modern Power Systems and Clean Energy, Vol6 (2018), No 2, p. 191-207. Details Full textCitation
• Ziel, Florian; Weron, Rafal: Day-ahead electricity price forecasting with high-dimensional structures: Univariate vs. multivariate modeling frameworks. In: Energy Economics, Vol70 (2018), p. 396-420. doi:10.1016/j.eneco.2017.12.016 Details Full textCitation
• Muniain, Peru; Ziel, Florian: Probabilistic forecasting and simulation of electricity prices. In: arXiv preprint arXiv:1810.08418 (2018). Details Full textCitation
• Uniejewski, Bartosz; Weron, Rafal; Ziel, Florian: Variance Stabilizing Transformations for Electricity Spot Price Forecasting. In: IEEE Transactions on Power Systems, Vol99 (2017), No 1. doi:10.1109/TPWRS.2017.2734563 Details Full textCitation
• 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.2017.0626 Details Citation
• 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.2017.7981900 Details Full textCitation
• Ziel, Florian: Forecasting Electricity Spot Prices Using Lasso: On Capturing the Autoregressive Intraday Structure. In: IEEE Transactions on Power Systems, Vol31 (2016), No 6, p. 4977-4987. doi:10.1109/TPWRS.2016.2521545 Details Full textCitation
• Ziel, Florian; Steinert, Rick: Electricity price forecasting using sale and purchase curves: The X-Model. In: Energy Economics, Vol59 (2016), p. 435-454. doi:10.1016/j.eneco.2016.08.008 Details Full textCitation
• Ziel, Florian; Croonenbroeck, Carsten; Ambach, Daniel: Forecasting wind power - Modeling periodic and non-linear effects under conditional heteroscedasticity. In: Applied Energy, Vol177 (2016), p. 285-297. doi:10.1016/j.apenergy.2016.05.111 Details Full textCitation
• Ziel, Florian: Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes. In: Computational Statistics & Data Analysis, Vol100 (2016), p. 773-793. doi:10.1016/j.csda.2015.11.016 Details Full textCitation
• Ziel, Florian; Liu, Bidong: Lasso estimation for GEFCom2014 probabilistic electric load forecasting. In: International Journal of Forecasting, Vol32 (2016), No 3, p. 1029-1037. doi:10.1016/j.ijforecast.2016.01.001 Details Full textCitation
• 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.2015.7477217 Details Full textCitation
• 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, Vol51 (2015), p. 430-444. doi:10.1016/j.eneco.2015.08.005 Details Full textCitation
• 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_23 Details Full textCitation
• Ziel, Florian; Steinert, Rick; Husmann, Sven: Efficient modeling and forecasting of electricity spot prices. In: Energy Economics, Vol47 (2015), p. 98-111. doi:10.1016/j.eneco.2014.10.012 Details Full textCitation

Talks:

• Ziel, Florian: Generating And Evaluating Probabilistic Forecasts - A Tutorial. ISF 2024, 1st Jul 2024, Dijon, France.
• Ziel, Florian: Electricity Price Forecasting. DLR Seminar, 8th May 2024, Virtual, Cottbus.
• Ziel, Florian: Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Price Forecasting. SMSA 2024, 12th Mar 2024, TU Delft.
• Ziel, Florian: Trading in hourly and quarter-hourly electricity price auctions. Economics Seminar, 10th Jan 2024, Essen.
• Ziel, Florian: Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Price Forecasting. Statistische Woche, 4th Sep 2023, Dortmund.
• Ziel, Florian: Electricity Price Forecasting: Data Science Meets Fundamental Models. 6th Energy Finance Italia, 8th Feb 2023, Milan, Italy.
• Ziel, Florian: Multivariate CRPS Learning. 42th International Symposium on Forecasting (ISF2022), 13th Jul 2022, Oxford, UK.
• Ziel, Florian: CRPS Learning. RuhrMetrics Seminar 2022, 24th Jun 2022, Bochum, Germany.
• Ziel, Florian: Optimal Probabilistic Forecast Combination Using CRPS Learning. International Conference on Computational Finance (ICCF) 2022, 6th Jun 2022, Wuppertal, Germany.
• Ziel, Florian: Data Science Models Meet Fundamental Models: Modern Electricity Price Forecasting Approaches . Fundamental and Stochastic Models in Energy Systems (digital), 1st May 2022, Karlsruhe/Cottbus, Germany.
• Ziel, Florian: CRPS Learning. Energy Finance Seminar, 18th Apr 2022, Stolberg(Harz), Germany.
• Ziel, Florian: Western Power Distribution Data Challenge on Estimating Electric Vehicle Charger Demand. WPD Challenge #2 - Winner Presentation (digital), 15th Mar 2022, Bristol, UK.
• Ziel, Florian: The Impact of Renewable Energy Forecasts on Intraday Electricity Prices. IAEE Webinar (digital), 1st Mar 2022, New York, US.
• Ziel, Florian: High Resolution Peak Demand Estimation Challenge. WPD Challenge #1 - Winner Presentation (digital), 21st Jan 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, 6th May 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, 26th Oct 2020, Rio, Brasil.
• Ziel, Florian: Integrated day-ahead and intraday self-schedule bidding for energy storages using approximate dynamic programming. Digital GOR Workshop, 7th Oct 2020, Bochum, Germany.
• Ziel, Florian: Forecasting Combination in Energy Forecasting. Strommarkttreffen - Machine Learning, 10th Apr 2020, Berlin, Germany (canceled due to COVID19).
• Ziel, Florian: Electricity Load Nowcasting. Energy Finance Seminar, 1st Apr 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, 25th Mar 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, 11th Mar 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, 12th Dec 2019, Dublin, Ireland.
• Ziel, Florian: Stochastic/Statistical Modelling of Electricity Prices. Hybrid Modelling of Energy Systems, 14th Nov 2019, Karlsruhe, Germany.
• Ziel, Florian: Combined Portfolio Rules under Parameter Uncertainty. Energy Finance Seminar, 18th Apr 2019, Stolberg(Harz), Germany.
• Ziel, Florian: Load and price forecasting. TenneT, 10th Apr 2019, Bayreuth, Germany.
• Ziel, Florian: Determining the Demand Elasticity in a Wholesale Electricity Market. Finance & Stochastics Research Seminar, 20th Mar 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, 14th Feb 2019, Cambridge, UK.
• Ziel, Florian: Determining the Demand Elasticity in a Wholesale Electricity Market. Energy Finance Christmas Workshop 2018, 12th Dec 2018, Bozen/Bolzano, Italy.
• Ziel, Florian: Probabilistic load forecasting. Strommarkttreffen, 24th Aug 2018, Berlin.
• Ziel, Florian: Marginal-Copula-Scores for Multivariate Forecasting Evaluation. Stochastisches Kolloquium, 21st Jun 2018, Siegen, Germany.
• Ziel, Florian: The impact of renewable energy forecasts on intra-day electricity prices. Strommarkttreffen, 1st Jun 2018, Berlin.
• Ziel, Florian: Conformal Prediction Interval Estimations with an Application to Day-Ahead and Intraday Power Markets. Computational Management Science (CMS 2018), 30th May 2018, Trondheim, Norway.
• Ziel, Florian: Modeling of the non-linear impact of renewable energy forecasts on intra-day electricity prices. Energy Finance Seminar, 18th Apr 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, 2nd Feb 2018, EDF, Paris, France.
• Ziel, Florian: Prognosen in Energiemärkten. Euroforum, 9th Jan 2018, Düsseldorf.
• Ziel, Florian: Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures.. CMStatistics 2017: Stochastic modelling of energy markets, 16th Dec 2017, London, UK.
• Ziel, Florian: Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures.. Energy Finance Christmas Workshop 2017, 14th Dec 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, 28th Nov 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), 1st Sep 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 , 27th Jun 2017, Cairns, Australia.
• Ziel, Florian: Public Holidays in Energy Forecasting. ISAE, International Symposium on Energy Analytics, 22nd Jun 2017, Cairns, Australia.
• Ziel, Florian: GEFCom2017. International Symposium on Energy Analytics, 22nd Jun 2017, Cairns, Australia.
• Ziel, Florian: Electricity price forecasting using sale and purchase curves: The X-Model. IAEE 2017 40th Annual IAEE International Conference, 19th Jun 2017, Singapore.
• Ziel, Florian: Electricity Price Forecasting Using Supply and Demand Curves. Economics Colloquium, RUB, 14th Jun 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, 8th Jun 2017, Dresden.
• Ziel, Florian: Probabilistic Mid- and Long-Term Electricity Price Forecasting: A supply and demand curves based approach. Energy Finance Seminar, 19th Apr 2017, Stolberg (Harz).
• Ziel, Florian: Einführung in das Verständnis von Zeitreihen. Mathematik-Wettbewerb 12.Klasse, 30th Mar 2017, C.F.Gauß-Gymnasium Frankfurt(Oder).
• Ziel, Florian: Prognose von Strompreisen. IUTA, 23rd Mar 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), 16th Mar 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, 1st Mar 2017, Reading, UK.
• Ziel, Florian: Modelling and Forecasting of Electricity Load. 13th Workshop on Stochastic Models, Statistics and Their Applications, 24th Feb 2017, HU Berlin.
• Ziel, Florian: Electricity Price Forecasting using Sale and Purchase Curves: The X- Model. Strommarkttreffen - Thema: Strompreismodellierung, 10th Feb 2017, Innogy, Berlin.

Tutored Theses:

• Day-Ahead Nachfrageprognose in Deutschland mit Zeitreihenmodellen (Bachelor Thesis Business Administration, 2025)
• Markowitz Portfolio Theory for Short-Term Electricity Markets (Master Thesis Business Administration, 2025)
• Auswirkungen von Pumpspeicherkraftwerken auf die Strompreise in Österreich (Bachelor Thesis Business Administration, 2025)
• Day-ahead electricity price forecasting in France using time series models (Bachelor Thesis Business Administration, 2025)
• Effects of battery usage on electricity prices (Bachelor Thesis Business Administration, 2025)
• Capture Preise und ihre Auswirkungen auf die Bewertung von Projekten im Bereich erneuerbare Energien (Bachelor Thesis Business Administration, 2025)
• Day-ahead Strompreisprognose in Deutschland unter Verwendung von Zeitreihenmodellen (Bachelor Thesis Business Administration, 2025)
• Day-ahead electricity price forecasting in Spain using time series models (Bachelor Thesis Business Administration, 2025)
• Gaspreisprognose unter der Verwendung von Zeitreihenmodellen (Bachelor Thesis Business Administration, 2025)
• Die Marktstabilitätsreserve im EU-Emissionshandelsystem (Bachelor Thesis Business Administration, 2025)
• Probabilistic Forecasting of European Electricity Prices (Master Thesis Econometrics, 2025)
• Investition in Wärmepumpen - Fallbeispiel: Schwimmbad (Bachelor Thesis Business Administration, 2025)
• Cascading in Energy Markets (Bachelor Thesis Business Administration, 2025)
• Deep Geothermal Heat Investments in the Upper Rhine Valley (Master Thesis Business Administration, 2024)
• Forecasting Electricity Price Using Distributional Neural Networks (Master Thesis Econometrics, 2024)
• Analyzing Weather Effects in Short-Term Load Forecasting Using Feed-Forward Neural Networks (Bachelor Thesis Econometrics, 2024)
• Schätzung der preisabhängigen Emissionsintensität des deutschen Kraftwerkparks mithilfe einer logistischen Regression (Bachelor Thesis Business Administration, 2024)
• Day-Ahead Electricity Price Forecasting Using GAMLSS (Master Thesis Econometrics, 2024)
• Hat die Nähe zu Handwerksbetrieben einen Einfluss auf den Zubau von kleinen Aufdach-Photovoltaik-Anlagen in NRW? (Bachelor Thesis Business Administration, 2024)
• Capacity Management in Multi-Tenant Data Centers: A Statistial Approach to Dynamical Tenant Utilization (Master Thesis Business Administration, 2024)
• Auswirkungen flexibler Stromtarife auf die Wirtschaftlichkeit von PV-Batteriesystemen (Bachelor Thesis Business Administration, 2024)
• Windkraftanlagentransport: Eine Kostenrechnungsperspektive (Bachelor Thesis Business Administration, 2024)
• Analyse der Kriterien beim Immobilienerwerb (Master Thesis Markets and Enterprises, 2024)
• Dunkelflauten im Kontext der Energieversorgungssicherheit (Bachelor Thesis Business Administration, 2024)
• Nachhaltige Mobilität im Fokus: Evaluierung der Wirtschaftlichkeit von Elektro-Batterie- und Wasserstoffantrieben (Bachelor Thesis Business Administration, 2024)
• Exploration der potenziellen Einflüsse von künstlicher Intelligenz auf die Kontrollmechanismen in Unternehmen: Eine Analyse unter Berücksichtigung der Arbeitsprozesse (Bachelor Thesis Business Administration, 2024)
• Vergleich ökologischer Aspekte von Nachhaltigkeitsberichten deutscher Automobilhersteller (Bachelor Thesis Business Administration, 2023)
• Analyse der Erdgasspeichersituation in Europa in 2022 (Bachelor Thesis Business Administration, 2023)
• Alternative Antriebssysteme – der direkte vergleich zwischen Elektro- und Wasserstoffautos (Bachelor Thesis Business Administration, 2023)
• Weltraumschrott: Problematik und Möglichkeiten zur Beseitung (Bachelor Thesis Business Administration, 2023)
• Nachhaltigkeit in Unternehmen – Eine Analyse am Beispiel des Nahrungsmittelkonzerns Nestlé (Bachelor Thesis Business Administration, 2023)
• Die Nutzung von Smart Metern in privaten Haushalten (Bachelor Thesis Business Administration, 2022)
• Kreislaufwirtschaft als Backstop-Technologie am Fallbeispiel Kunststoff (Bachelor Thesis Law, 2022)
• Herausforderung eines Wasserstoffmarktes (Bachelor Thesis Business Administration, 2022)
• Auswirkung von Treibhausemissionskosten auf den Produktionsstandort an einem Fallbeispiel (Bachelor Thesis Business Administration, 2022)
• Akzeptanz von Kernenergie in Europa (Bachelor Thesis Business Administration, 2022)
• Decision tree learning for modeling price auctions of day-ahead electricity markets (Master Thesis Business Administration - Energy and Finance, 2021)
• Simulation-based Forecasting of Intraday Power Prices (Master Thesis Business Administration - Energy and Finance, 2021)
• Intensive Landwirtschaft und deren Umweltauswirkungen im ökonomischen Kontext (Bachelor Thesis Business Administration - Energy and Finance, 2021)
• Welche Cryptocurrency ist hinsichtlich ihres Energieverbrauchs am effizientesten? (Bachelor Thesis Business Administration - Energy and Finance, 2021)
• Modelling the order book of the German (continuous) intraday electricity market (Master Thesis Business Administration - Energy and Finance, 2020)
• Short-term renewables position management in intraday electricity markets (Master Thesis Business Administration - Energy and Finance, 2020)
• Die CO₂-Steuer als Internalisierungsmaßnahme - eine theoretische Analyse (Bachelor Thesis Law, 2020)
• Data Science Methods for Probabilistic Natural Gas Price Forecasting (Master Thesis Business Administration - Energy and Finance, 2020)
• Die Betrachtung erneuerbarer Energien nach Ende des EEG Förderzeitraumes - Eine betriebswirtschaftliche Sicht (Bachelor Thesis Business Administration, 2020)
• Der Vergleich von Vergleichsportalen - ein Vergleich von qualitativen und quantitativen Merkmalen (Bachelor Thesis Business Administration, 2020)
• Die Einführung neuer Sektoren in ein bestehendes Emissionshandelssystem (Bachelor Thesis Business Administration - Energy and Finance, 2020)
• Die Mehrkosten des Ökostroms - Ein Kostenvergleich zwischen grauem und grünem Strom (Bachelor Thesis Economics, 2019)
• Autarke Stromversorgung von Insellösungen in Anlehnung an das Großprojekt "RedoxWind" (Bachelor Thesis Business Administration - Energy and Finance, 2019)
• The next trade - a continuous price model of the German intraday electricity market (Master Thesis Business Administration, 2019)
• Statistical analysis of the probability of scenarios for the German electricity market (Master Thesis Business Administration - Energy and Finance, 2019)
• Probabilistic Forecasting of Electrcity Prices using Derivative Data (Master Thesis Business Administration - Energy and Finance, 2019)
• Econometrics of the German day-ahead control reserve market (Master Thesis Econometrics, 2019)
• Wirtschaftlichkeitsvergleich eines Fuhrparks mit elektrischem und konventionellem Antrieb (Bachelor Thesis Business Administration, 2019)
• Kraftwerksbewertung im Hinblick auf CO₂-Emissionen (Bachelor Thesis Business Administration - Energy and Finance, 2019)
• Probabilistic Short-Term Water Demand Forecasting (Master Thesis Business Administration - Energy and Finance, 2019)
• Ökonometriche Modellierung der Treibhausgasemissionen in Europa (Master Thesis Econometrics, 2019)
• Verursachungsgerechte Abweichungsanalyse von Regressionsschätzungen als Analytisches Prüfungsverfahren (Master Thesis Business Administration - Energy and Finance, 2019)
• Combination of wind power forecasts using data science methods (Master Thesis Business Information Systems, 2018)
• Investitionen in Photovoltaikanlagen im Rahmen des EEG 2017 (Bachelor Thesis, 2018)
• Ausschreibungen von onshore Windparks und deren Finanzierung (Bachelor Thesis Business Administration - Energy and Finance, 2018)