Max Kleinebrahm

M. Sc. Max Kleinebrahm

Activities

Research interests

  • Analysis and modeling of decentralized energy systems
  • Energy self-sufficient residential buildings
    • Methods: optimization, clustering
  • Modeling of resident behavior (activity and mobility patterns)
  • Generation of synthetic data (sequences, time series)
    • Methods: neural networks (Transformer, GAN, LSTM, MDN, TCN), Markov chains, differential privacy

Projects

Teaching

  • Supervision of the seminar "Effects of the increased integration of renewable energies in future energy worlds" (WiSe 2017/2018, SoSe 2018, WiSe 2018/2019)
  • Supervision of Bachelor and Master theses (have a look here)

Profile

  • Research assistant at the Chair of Energy Economics since March 2017
  • Bachelor's and master's degree in industrial engineering specializing in mechanical engineering / energy technology at RWTH Aachen University and the Norwegian University of Science and Technology (NTNU)
  • Experience as an intern at Drees & Sommer Advanced Building Technologies GmbH, German University of Technology (GUTech) in Oman and as a student assistant at the Fraunhofer Institute for Production Technology (IPT) at RWTH Aachen University
  • Research stay at the University of Reading as a CREDS Visitor

Veröffentlichungen


The impact of public acceptance on cost efficiency and environmental sustainability in decentralized energy systems.
Weinand, J. M.; McKenna, R.; Kleinebrahm, M.; Scheller, F.; Fichtner, W.
2021. Patterns, 2 (7), Art.-Nr.: 100301. doi:10.1016/j.patter.2021.100301
Research trends in combinatorial optimization.
Weinand, J. M.; Sörensen, K.; San Segundo, P.; Kleinebrahm, M.; McKenna, R.
2021. International transactions in operational research, itor.12996. doi:10.1111/itor.12996
Development of a dynamic European residential building stock typology for energy system analysis.
Kleinebrahm, M.; Naber, E.; Weinand, J.; McKenna, R.; Ardone, A.
2021, April 19. European Geosciences Union General Assembly (EGU 2021), Online, April 19–30, 2021. doi:10.5194/egusphere-egu21-8001
Using neural networks to model long-term dependencies in occupancy behavior.
Kleinebrahm, M.; Torriti, J.; McKenna, R.; Ardone, A.; Fichtner, W.
2021. Energy and buildings, 240, Art.Nr. 110879. doi:10.1016/j.enbuild.2021.110879
Identification of Potential Off-Grid Municipalities with 100% Renewable Energy Supply for Future Design of Power Grids.
Weinand, J. M.; Ried, S.; Kleinebrahm, M.; McKenna, R.; Fichtner, W.
2020. IEEE transactions on power systems. doi:10.1109/TPWRS.2020.3033747
Using neural networks to model long-term dependencies in occupancy behavior.
Kleinebrahm, M.; Torriti, J.; McKenna, R.; Ardone, A.; Fichtner, W.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000126271
Identification of potential off-grid municipalities with 100% renewable energy supply.
Weinand, J. M.; Ried, S.; Kleinebrahm, M.; McKenna, R.; Fichtner, W.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000118013
Developing a combinatorial optimisation approach to design geothermal-based district heating systems.
Weinand, J. M.; Kleinebrahm, M.; McKenna, R.; Mainzer, K.; Fichtner, W.
2019, June 26. 30th European Conference on Operational Research (EURO 2019), Dublin, Ireland, June 23–26, 2019
Effects of the tenants electricity law on energy system layout and landlord-tenant relationship in a multi-family building in Germany.
Braeuer, F.; Kleinebrahm, M.; Naber, E.
2019. IOP conference series / Earth and environmental science, 323, Art.-Nr.: 012168. doi:10.1088/1755-1315/323/1/012168
Developing a combinatorial optimisation approach to design district heating networks based on deep geothermal energy.
Weinand, J. M.; Kleinebrahm, M.; McKenna, R.; Mainzer, K.; Fichtner, W.
2019. Applied energy, 251, 113367. doi:10.1016/j.apenergy.2019.113367
Developing a three-stage heuristic to design geothermal-based district heating systems.
Weinand, J.; Kleinebrahm, M.; McKenna, R.; Mainzer, K.; Fichtner, W.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000090290
Optimal Renewable Energy Based Supply Systems for Self-sufficient Residential Buildings.
Kleinebrahm, M.; Weinand, J.; Ardone, A.; McKenna, R.
2018. BauSIM2018 - 7. Deutsch-Österreichische IBPSA-Konferenz : Tagungsband. Hrsg.: P. von Both, 164–171, Karlsruher Institut für Technologie (KIT)
A stochastic multi-energy simulation model for UK residential buildings.
McKenna, R.; Hofmann, L.; Kleinebrahm, M.; Fichtner, W.
2018. Energy and buildings, 168, 470–489. doi:10.1016/j.enbuild.2018.02.051

Conferences

Conference/workshop proceedings:

Exploring socioeconomic and temporal characteristics of British and German residential energy demand. McKenna, R.; Kleinebrahm, M.; Yunusov, T.; Lorincz, M.; Torriti, J. British Institute of Energy Economics 2018, 18-19 September 2018, Oxford, UK.

 

Using attention to model long-term dependencies in occupancy behavior. Kleinebrahm, M.; Torriti, J.; McKenna, R.; Ardone, A.; Fichtner, W. Tackling Climate Change with Machine Learning workshop at NeurIPS 2020.

 

Presentations:

Weinand, J.; Kleinebrahm, M.; Mainzer, K.; McKenna, R. (2018): Exploring the technical and economic feasibility of complete municipal energy autonomy: A case study for Germany, 41st IAEE International Conference, 10-13 June, Groningen, Netherlands.