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Schlüter, Stephan, Prof. Dr.

Stephan Schlüter

Professor Dr.

Head of the Research Group for Applied Mathematics for Energy Markets

Link to the research group


Fields of Interest:
  • Multivariate time series analysis
  • Statistical analysis and modelling of energy commodities
  • Time series forecasting
  • Renewable energies
  • Environmental Statistics
  • Big Data

Currently I'm a Co-Editor of the Journal Spatial Information Research.


  • Höhere Mathematik
  • Operations Research
  • Statistik
  • Stochastik
  • Angewandte Zeitreihenanalyse
  • ...

Ich habe immer Themen für Studien-, Bachelor- oder Masterarbeiten. Bitte wenden Sie sich diesbezüglich per eMail oder persönlich an mich.

Publications and Paper

Current Working Paper

Kojic M, Mitic, P, Schlüter S, Rakic S (2023). Crises impact on interdependence between conventional and green bonds markets. Working Paper. Submitted.

Schlüter S, Pappert S, Neumann M (2023). Interval Forecasts for Gas Prices in the Face of Structural Breaks – Statistical Models vs. Neural Networks. Working Paper. Submitted.

Jung S, Heinzelmann L, Liebert T, Schlüter S, Lee W H (2023): High-rise Building Detection: Testing a New Object-Based Approach against Neural Networks. Working Paper. Submitted.

Published Articles

von Döllen A, Schlüter S (2024): Heat Pumps for Germany – Additional Pressure on the (Renewable) Supply-Demand Equilibrium and How to Cope with Hydrogen. Energies, 17(12), 3053;

Hwang Y-S, Um Y-S,Pradhan B, Choudhury T, Schlüter S (2023): How does ChatGBT evaluate the value of spatial information in the 4th industrial revolution? Spatial Information Research.

Mitić P, Kojić M, Hanić A, Schlüter S. Environment and Economy Interactions in the Western Balkans: Current Situation and Prospects (2023). In: Tufek-Memišević, T., Arslanagić-Kalajdžić, M., Ademović, N. (eds) Interdisciplinary Advances in Sustainable Development. ICSD 2022. Lecture Notes in Networks and Systems, vol 529. Springer, Cham.

Hwang Y-S, Schlüter S, Um J-S. Cross-correlation of GOSAT CO2 Concentration with Repeated Heat-Wave-induced Photosynthetic Inhibition in Europe from 2009 to 2017. Remote Sensing, 2022. URL:

Schlüter S, Jung S,  von Döllen A, Lee W. An Alternative to Index-Based Gas Sourcing Using Neural Networks. Energies, 2022, 15, 4708. . 

Kojić M, Schlüter S, Mitić P, Hanić A. Economy-environment nexus in developed European countries: Evidence from multifractal and wavelet analysis. Chaos, Solitons and Fractals, 2022, 160, 112189.

Schlüter S, Menz F, Kojić M, Mitić P, Hanić A. A Novel Approach to Generate Hourly Photovoltaic Power Scenarios. Sustainability, 2022, 14, 4617. https://

Hwang Y-S, Schlüter S, Park S-I, Um J-S. Comparative Evaluation for Tracking the Capability of Solar Cell Malfunction Caused by Soil Debris between UAV Video versos Photo-Mosaic. Remote Sensing, 2022, 14, 1220.

Hwang Y-S, Roh J W, Suh D, Otto M-O, Schlüter S, Choudhurry T, Huh J-S. No Evidence for Global Decrease in CO2 Concentration During the First Wave of COVID‑19 Pandemic. Environmental Monitoring and Assessment, 2021, 193:751.

von Döllen A, Hwang Y, Schlüter S. The Future Is Colorful—An Analysis of the CO2 Bow Wave and Why Green Hydrogen Cannot Do It Alone. Energies 2021, 14, 5720.

Hwang Y, Schlüter S, Choudhury, T, Um J-S. Comparative Evaluation of Top-Down GOSAT XCO2 vs. Bottom-Up National Reports in the European Countries. Sustainability, 2021.

Liebermann S, Um J-S, Hwang Y, Schlüter, S. Performance Evaluation of Neural Network-Based Short-Term Solar Irradiation Forecasts. Energies 2021, 14, 3030. DOI:

Hwang Y, Um J-S,  Hwang J, Schlüter S. Evaluating the Causal Relations between the Kaya Identity Index and ODIAC-Based Fossil Fuel CO2 Flux. Energies 2020. .

Kreuzer D, Schlüter S, Munz M. Short-term temperature forecasts using a convolutional neural network — An application to different weather stations in Germany. Machine Learning with Applications 2020, 2,

Hwang Y, Um J-S, Schlüter S. Evaluating the Mutual Relationship between IPAT/Kaya Identity Index and ODIAC-Based GOSAT Fossil-Fuel CO2 Flux: Potential and Constraints in Utilizing Decomposed Variables. Int. J. Environ. Res. Public Health 2020, 17, 5976.

Schlüter S, Kresoja M. Two Preprocessing Algorithms for Climate Time Series. Journal of Applied Statistics 2019,
Schlüter S. A sine-based Model for the Volatility of Daily Photovoltaic Production. Working Paper, 2017.

Hanfeld M, Schlüter S. Operating a Swing Option on Today's Gas Markets - How Least Squares Monte Carlo Works and Why it is Beneficial. Zeitschrift für Energiewirtschaft, 2:137-145, 2017.

Herwartz H, Schlüter S. On the Predictive Information of Futures' Price - a Wavelet Based Assessment. Journal of Forecasting, 2016.

Schlüter S, Deuschle C. Wavelet-Based Forecasting of ARIMA Time Series - an Empirical Comparison of Different Methods. Managerial Economics, 15(1):107-131, 2015.

Schlüter S, Hanfeld M. Pricing Asian Oil Options using Polynomial Quantile Functions. IEEE Conference Proceedings of the EEM 2014, Krakow, 2014.

Schlüter S, Fischer M. A Tail Quantile Approximation for the Student T Distribution. Communications in Statistics: Theory and Methods, 41(15):2617-2625, 2012.

Schlüter S, Fischer M. The Weak Tail Dependence Coefficient of the Elliptical Generalized Hyperbolic Distribution. Extremes,  04 2011.

Schlüter S. A Long-Term/Short-Term Model for Daily Electricity Prices with Dynamic Volatility. Energy Economics, 32(5):1074-1081, 2010.

Fischer M, Köck C, Schlüter S, Weigert F. An Empirical Analysis of Multivariate Copula Models. Quantitative Finance, 9(7):839-854, 2009.

Currently Supervised Students

Abhinav Das (PhD)

Erick Michel Lara Pinal (PhD)

Martin Neumann (Master)

Andreas Lebedev (Master)

Prof. Dr. Stephan Schlüter
Raum: B207
Prittwitzstraße 10
89075 Ulm
Fon: +49 731 96537-584