Program for stream Modelling & Analytics for Energy Economics II

MA-08: Statistical and Deep Learning Techniques for Energy Time Series
Stream: Modelling & Analytics for Energy Economics II
Room: A008
Chair(s): Dogan Keles

• Can Time-Series Methods Improve the Accuracy of the Wind Energy Forecasts? Evidence from Ireland
  Kevin Forbes, Ernest Zampelli
• Artificial Neural Networks in EPF: Are deep structures beneficial?
  Grzegorz Marcjasz
• Stochastic simulation of spatial-temporal correlated renewable feed-in series
  Benjamin Böcker
• Modeling of Control Reserve Prices using Econometric and Artificial Intelligence Approaches
  Emil Kraft, Dogan Keles

MB-08: Modelling approaches to speed-up energy system models: Heuristics and exact methods
Stream: Modelling & Analytics for Energy Economics II
Room: A008
Chair(s): Frieder Borggrefe

• Performance analysis of selected conceptual speed-up methods to improve computation time of energy system models
  Kai von Krbek, Karl-Kiên Cao
• Acceleration strategies for speeding up the solution time of the TIMES energy systems model generator – findings from the BEAM-ME project
  Evangelos Panos, Aymane Hassan
• Reducing Energy Time Series for Energy System Models via Self-Organizing Maps
  Dogan Keles, Hasan Ümitcan Yilmaz, Edouard Fouché, Thomas Dengiz
• How to speed-up computing time of energy system models: key findings from the BEAM-ME project
  Frieder Borggrefe, Olexandr Balyk, Stefanie Buchholz, Hannes Hobbie, Samir Jeddi, Robin Leisen, Evangelos Panos, David Schönheit