DFG Research Training Group 2153: "Energy Status Data - Informatics Methods for its Collection, Analysis and Exploitation"
Thomas Dengiz

M.Sc. Thomas Dengiz

  • Institut für Industriebetriebslehre und Industrielle Produktion (IIP)

    Westhochschule Gebäude 06.33 
    Hertzstr. 16
    76187 Karlsruhe

    Raum 012

Research Abstract

The goal of my study is to quantify the flexibility of electrical heat supply in German households as a function of the various influencing factors like outside temperature, building insulation, heating technologies used and comfort level of the residents. For achieving this aim a model of a single building and of a residential area will be set up. This flexibility – together with data-driven supply forecasts – will be used to react to times when an oversupply of power produced by the volatile renewable energy sources is observable in the grid. By doing so we can estimate how much flexibility is necessary in order to avoid oversupply in certain areas in Germany (e.g. Schleswig-Holstein). Moreover, we aim to calculate the required macroeconomic investments to avoid excess energy in Germany by using different power-to-heat-systems. Those numbers will then be compared to the ones of other flexibility options like electric vehicles or batteries.

Research Interests

  • Operations Research and Optimisation
  • Energy System Analysis
  • Application of Data Mining and Machine Learning


Optimization approaches for exploiting the load flexibility of electric heating devices in smart grids. PhD dissertation.
Dengiz, T.
2021, April 14. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000131495
Aggregating load shifting potentials of electric vehicles for energy system models.
Ried, S.; Dengiz, T.; Soldner, S.; Jochem, P.
2020. 17th International Conference on the European Energy Market, EEM 2020, Stockholm, Sweden, 16 - 18 September 2020, Art.Nr. 9221974, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EEM49802.2020.9221974
Demand response through decentralized optimization in residential areas with wind and photovoltaics.
Dengiz, T.; Jochem, P.; Fichtner, W.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000118359
Uncertainty handling control algorithms for demand response with modulating electric heating devices.
Dengiz, T.; Jochem, P.; Fichtner, W.
2019. 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Bucharest, RO, September 29 - October 2, 2019, Article no: 8905448, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEurope.2019.8905448
Reducing energy time series for energy system models via self-organizing maps.
Yilmaz, H. Ü.; Fouché, E.; Dengiz, T.; Krauß, L.; Keles, D.; Fichtner, W.
2019. Information technology, 61 (2-3), 125–133. doi:10.1515/itit-2019-0025
Demand response with heuristic control strategies for modulating heat pumps.
Dengiz, T.; Jochem, P.; Fichtner, W.
2019. Applied energy, 238, 1346–1360. doi:10.1016/j.apenergy.2018.12.008
Impact of different control strategies on the flexibility of power-to-heat-systems.
Dengiz, T.; Jochem, P.; Fichtner, W.
2018. Transforming Energy Markets : 41st IAEE International Conference, Groningen, Netherlands, 11th - 13th June, 2018, International Association for Energy Economics
Comparison of Multi-objective Evolutionary Optimization in Smart Building Scenarios.
Braun, M.; Dengiz, T.; Mauser, I.; Schmeck, H.
2016. Applications of Evolutionary Computation (EvoApplications) : 19th European Conference, Proceedings Part 1, Porto, Portugal, 30th March - 1st April 2016. Ed.: G. Squillero, 443–458, Springer Verlag. doi:10.1007/978-3-319-31204-0_29