M.Sc. Tim Janke

M.Sc. Tim Janke
Landgraf-Georg-Str. 4
64283 Darmstadt

Building S3|10, Office: 305
Telephone Office: +49 (0) 6151 16-21714
Telefax: +49 (0) 6151 16-21712

tim.jankfanze@einh6s.tu-dar9d0mstadt.dekjrg
Janke

Research Interest

General research interests:

  • Machine learning and data analysis in the energy domain
  • Uncertainty quantification
  • Probabilistic forecasting
  • Energy market design & regulation

Current project: probabilistic price forecasting for electricity markets

In the course of the Energiewende the share of renewable energy sources (RES) in the total electricity generation has steadily increased. One main characteristic of RES is their dependence on the given supply, i.e. solar radiation or wind speed, which renders the expected production from these sources volatile and uncertain. This motivates the efforts currently undertaken to increase the ability of the demand side to react flexible to the increasingly volatile generation. Furthermore, the markets for energy and power gained in importance. Market prices play the key role for the effective and efficient coordination of the volatile and uncertain generation from RES, the thermal generation, and the flexible share of the demand. Operators of flexibility options, such as storages, industrial processes, gas turbines, or heat pumps, must decide at all times on bid prices and quantities as well as on the market at which they place their offer under an uncertain future market price. Hence, the operators face a complex stochastic optimization problem with the market price as the key parameter.

Therefore, the goal of the project is to develop and validate methods and algorithms for the reliable probabilistic forecasting of electricity prices for several markets. A probabilistic forecast, i.e. a forecast of a probability distribution for each point in time instead of just a single, most likely value, enables the application of stochastic optimization methods because it allows the incorporation the of uncertainty of the prediction. This is especially relevant in times of high volatility or extreme prices events. The developed methods should help to encourage and facilitate the active participation of small and medium sized suppliers, prosumers, and consumers in modern energy markets.

The project is done in cooperation with the Entega AG and funded by the TU Darmstadt Pioneer Fund.

            

Short Bio

  • Since 2017: PhD student at EINS

  • 2013 – 2017: M.Sc. Business Administration/Industrial Engineering at TU Darmstadt and University of Bergamo

  • 2008 – 2013: B.Sc. Business Administration/Industrial Engineering at TU Darmstadt

Veröffentlichungen

2018

  • Beykirch, M.; Janke, T.; Steinke, F.: Learning Dispatch Parameters of Thermal Power Plants from Observations, 8th IEEE PES Innovative Smart Grid Technologies Conference Europe, (2018)
  • Janke, T.; Brindley, B.; Rodemann, T.; Steinke, F.: Incentivizing the adoption of local flexibility options: A quantitative case study, 15th International Conference on the European Energy Market (EEM), (2018)
Print | Legal note | Privacy Policy | Sitemap | Search | Contact
to topto top