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

Multivariate time series imputation for energy data using neural networks
Bülte, C.; Kleinebrahm, M.; Yilmaz, H. Ü.; Gómez-Romero, J.
2023. Energy and AI, 13, Artikl.Nr.: 100239. doi:10.1016/j.egyai.2023.100239

Analysing municipal energy system transformations in line with national greenhouse gas reduction strategies
Kleinebrahm, M.; Weinand, J. M.; Naber, E.; McKenna, R.; Ardone, A.
2023. Applied Energy, 332, Art.-Nr.: 120515. doi:10.1016/j.apenergy.2022.120515

Corrigendum to “Assessing the contribution of simultaneous heat and power generation from geothermal plants in off-grid municipalities” [Appl. Energy 255 (2019) 113824]
Weinand, J. M.; McKenna, R.; Kleinebrahm, M.; Mainzer, K.
2022. Applied Energy, 307, Art.-Nr.: 118202. doi:10.1016/j.apenergy.2021.118202

Dissemination of PV-Battery systems in the German residential sector up to 2050: Technological diffusion from multidisciplinary perspectives
Vogele, S.; Poganietz, W.-R.; Kleinebrahm, M.; Weimer-Jehle, W.; Bernhard, J.; Kuckshinrichs, W.; Weiss, A.
2022. Energy, 248, Artk.Nr.: 123477. doi:10.1016/j.energy.2022.123477

Optimal system design for energy communities in multi-family buildings: the case of the German Tenant Electricity Law
Braeuer, F.; Kleinebrahm, M.; Naber, E.; Scheller, F.; McKenna, R.
2022. Applied Energy, 305, Art.-Nr.: 117884. doi:10.1016/j.apenergy.2021.117884

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.
2022. International transactions in operational research, 29 (2), 667–705. 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. vEGU21: 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

Assessing the contribution of simultaneous heat and power generation from geothermal plants in off-grid municipalities
Weinand, J. M.; McKenna, R.; Kleinebrahm, M.; Mainzer, K.
2019. Applied energy, 255, 113824. doi:10.1016/j.apenergy.2019.113824

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, 41^stIAEE International Conference, 10-13 June, Groningen, Netherlands.

Kachirayil, F.; McKenna, R.; Weinand, J.; Kleinebrahm, M.; Huckebrink, D.; Bertsch, V. (2021): Quantifying the trade-off between cost and security of supply for 100% renewable local energy systems. ProMETS Workshop: Prospektive multidimensionale Bewertung von Energietechnologien und -szenarien, 25-26 Feburary, Oldenburg, Germany

Kleinebrahm, M., Naber, E., Weinand, J., McKenna, R., and Ardone, A.: Development of a dynamic European residential building stock typology for energy system analysis, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8001, https://doi.org/10.5194/egusphere-egu21-8001, 2021.

Weinand, J., McKenna, R., Kleinebrahm, M., and Scheller, F.: Quantifying the trade-off between public acceptance and cost efficiency in decentralized energy systems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-716, https://doi.org/10.5194/egusphere-egu21-716, 2021.

Kleinebrahm, M. (2021): Synthetic data for a better understanding of residential energy demand - Synthetic Data Meetup Webinar - https://mostly.ai/2021/04/27/synthetic-data-for-residential-energy/