Curriculum Vitae:

Projects:

StoOpt.NRW

Publications:

• Beran, P.; Vogler, A.; Weber, C.: Multi-day-ahead Electricity Price Forecasting: A Comparison of fundamental, econometric and hybrid Models, 02/2021. Essen 2021. Full textCitationDetails
• Vogler, A.; Ziel, F.: On the Evaluation of Binary Event Probability Predictions in Electricity Price Forecasting, 11/2019. Essen 2019. Full textCitationDetails
• Beran, P.; Furtwängler, C.; Jahns, C.; Syben, O.; Vogler, A.; Warszawski, M.; Weber, C.: IT-Werkzeuge und -Systeme für die nachhaltige Bewirtschaftung von KWK- und Speichersystemen - Stochastische Optimierung von Multi-Asset-Systemen in NRW (StoOpt.NRW), Aachen, Essen 2019. Full textCitationDetails
• Beran, P.; Vogler, A.; Weber, C.: Kurz- und mittelfristige Preisprognosen: Auswahl optimaler Modellierungsansätze unter Berücksichtigung des Prognosehorizonts, VDI-Berichte, 2303. GmbH, Vdi Wissensforum (Ed.), Würzburg 2017. CitationDetails
• Pape, C.; Vogler, A.; Woll, O.; Weber, C.: Forecasting the distributions of hourly electricity spot prices - Accounting for serial correlation patterns and non-normality of price distributions, 05/2017. Essen 2017. Full textCitationAbstractDetails

  We present a stochastic modelling approach to describe the dynamics of hourly electricity prices. The suggested methodology is a stepwise combination of several mathematical operations to adequately characterize the distribution of electricity spot prices. The basic idea is to analyze day-ahead prices as panel of 24 cross-sectional hours and to identify principal components of hourly prices to account for the cross correlation between hours. Moreover, non-normality of residuals is addressed by performing a normal quantile transformation and specifying appropriate stochastic processes for time series before fit. We highlight the importance of adequate distributional forecasts and present a framework to evaluate the distribution forecast accuracy. The application for German electricity prices 2015 reveal that: (i) An autoregressive specification of the stochastic component delivers the best distribution but not always the best point forecasting results. (ii) Only a complete evaluation of point, interval and density forecast, including formal statistical tests, can ensure a correct model choice.

Tutored Theses:

• Kurz- und mittelfristige Strompreisprognose über variierende Prognosehorizonte mit einem hybriden Modellierungsansatz (Master Thesis Business Administration - Energy and Finance, 2018)