KONSENS: Konsistente Optimierung und Stabilisierung
elektrischer Netzwerksysteme

TU Chemnitz TU Ilmenau MPI Magdeburg

Duration: February 2018 - June 2021

Support: Bundesministerium für Bildung und Forschung - "Mathematik für Innovationen" als Beitrag zur Energiewende

Press Release: TU Chemnitz - Uni aktuell (04/2018). Mit mathematischen Modellen zur Energiewende beitragen

    Algorithmic and Discrete Mathematics
  • Prof. Dr. Christoph Helmberg (Project Coordinator)
    Technische Universität Chemnitz
    Straße der Nationen 62, 09107 Chemnitz
  • Dr. Bartosz Filipecki

The energy transition comes along with more and more volatile generators (renewable energy sources), flexible consumers (e-mobility) as well as novel energy storages (batteries, heat accumulators). Thus, new challenges have to be faced on the one hand, but also new opportunities can be explored on the other. Currently, potential flexibilities cannot be exploited within the traditional half-automated system management of the grid operators. New mathematical methods and concepts are required in order to handle the interaction from the transmission grid through the distribution grid to the microgrid in a fully automated fashion.
The goal of this project is to develop mathematical optimization methods to exploit flexibilities on all levels of the electricity grid within the power flow optimization while ensuring security and stability. To this end, it is essential to focus on the core elements to generate mathematically manageable models.

The year 2020 is coined by the coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Starting in May 2020 the KONSENS consortium also aims to contribute to provide information on the spread of the disease and evaluate countermeasures. Here, the key is the versatile nature of the mathematical methods. For this second branch of the project the team is supported by Prof. Dr. Thomas Hotz and Stefan Heyder from the Group for Probability Theory and Mathematical Statistics of the department for mathematics at Technische Universität Ilmenau.


The first goal of this project is to develop mathematical methods and algorithms for the optimization and stabilization of the electrical power grid with emphasis on new technological developments such as the rise of renewables, E-mobility, and others. Furthermore, in the course of the extension of the project towards epidemic research, models to predict the evolution of the COVID-19 pandemic and to study the impact of countermeasures are developed. All results are reported in scientific publications:

  • T. Aschenbruck, W. Esterhuizen, J. Dickert, B. Filipecki, S. Grundel, C. Helmberg, T.K.S. Ritschel, P. Sauerteig, S. Streif, A. Wasserrab, K. Worthmann
    Exploiting Flexibility from Residential Batteries throughout the Power Grid
  • S. Grundel, S. Heyder, T. Hotz, T.K.S. Ritschel, P. Sauerteig, K. Worthmann
    How to Coordinate Vaccination and Social Distancing to Mitigate SARS-CoV-2 Outbreaks
    SIAM Journal on Applied Dynamical Systems, 20(2), 1135-1157 (2021)
  • S. Grundel, S. Heyder, T. Hotz, T.K.S. Ritschel, P. Sauerteig, K. Worthmann
    How much testing and social distancing is required to control COVID-19? Some insight based on an age-differentiated compartmental model
    Provisionally accepted for publication in SIAM Journal on Control and Optimization, preprint available at https://arxiv.org/abs/2011.01282
  • Y. Jiang, P. Sauerteig, B. Houska, K. Worthmann
    Distributed Optimization using ALADIN for Model Predictive Control in Smart Grids
    IEEE Transactions on Control Systems Technology 29(5), 2142-2152 (2021)
  • T.K.S. Ritschel, F. Weiss, M. Baumann, S. Grundel
    Nonlinear model reduction of dynamical power grid models using quadratization and balanced truncation
    at - Automatisierungstechnik 68(12), 1022-1034 (2020, DOI: 10.1515/auto-2020-0070)
  • T. Aschenbruck, W. Esterhuizen, S. Streif
    Transient stability analysis of power grids with admissible and maximal robust positively invariant sets
    at - Automatisierungstechnik (2020). In Press
  • P. Sauerteig, K. Worthmann
    Towards multiobjective optimization and control of smart grids.
    Optimal Control, Applications and Methods (OCAM), special issue "MPC for Energy Systems: Economic and Distributed Approaches", 41:128-145 (2020)
  • W. Esterhuizen, T. Aschenbruck, S. Streif
    On Maximal Robust Positively Invariant Sets in Constrained Nonlinear Systems,
    Automatica 119, 109044 (2020)
  • M. Baumann, S. Grundel, P. Sauerteig, K. Worthmann
    Surrogate models in bidirectional optimization of coupled microgrids.
    at-Automatisierungstechnik, 67(12), 1035-1046 (2019)
  • P. Sauerteig, W. Esterhuizen, M. Wilson, T. K. S. Ritschel, K. Worthmann, S. Streif
    Model Predictive Control Tailored to Epidemic Models
    Accepted for publication (and presentation at the European Control Conference 2022 in London).
  • T. Aschenbruck, M. Baumann, W. Esterhuizen, B. Filipecki, S. Grundel, C. Helmberg, P. Sauerteig, S. Streif, T.K.S. Ritschel, K. Worthmann
    Optimization and Stabilization of Hierarchical Electrical Networks
    In S. Göttlich, M. Herty, and A. Milde, editors, Mathematical Modeling, Simulation, and Optimization for Power Engineering and Management, Springer, 171-198, 2021
  • P. Sauerteig, M. Baumann, J. Dickert, S. Grundel, K. Worthmann
    Reducing transmission losses via reactive power control
    In S. Göttlich, M. Herty, and A. Milde, editors, Mathematical Modeling, Simulation, and Optimization for Power Engineering and Management, Springer, 219-232, 2021
  • P. Sauerteig, Y. Jiang, B. Houska, K. Worthmann
    Distributed Control Enforcing Group Sparsity in Smart Grids
    IFAC-PapersOnLine, 53(2), 13269-13274, 2020.
  • S. Grundel, P. Sauerteig, K. Worthmann
    Surrogate models for coupled microgrids
    In I. Faragó, F. Izsák, P.L. Simon, editors, Progress in Industrial Mathematics at ECMI 2018, volume 30 of Mathematics in Industry, Springer, 477-483, 2019.
  • P. Braun, P. Sauerteig, K. Worthmann
    Distributed optimization based control on the example of microgrids
    In M.J. Blondin, P.M. Pardalos, and J. Saéz, editors, Computational Intelligence and Optimization Methods for Control Engineering, volume 150 of Springer Optmization and Its Applications, Springer, 173-200, 2019.

Project meetings

The industrial and academic partners (used to) have regular project meetings with alternating hosts. In the course of the pandemic the in-person meetings have been replaced by more frequent virtual meetings. In particular, the academic researchers meet on a weekly basis.

In-person meetings

  • 10.03.2020 - Lunch-to-lunch meeting at TU Chemnitz [all partners]
  • 01.10.2019 - Progress meeting at TU Ilmenau [all partners]
  • 27.03.2019 - Meeting at Venios GmbH in Frankfurt am Main [all partners]
  • 17.01.2019 - Modelling workshop at ENSO NETZ GmbH in Dresden [MPI, TUIl, ENSO]
  • 03.12.2018 - Progress meeting at ENSO NETZ GmbH in Dresden [all partners]
  • 06.09.2018 - Modelling workshop at TenneT Bayreuth [all partners]
  • 09.07.2018 - Progress meeting at MPI Magdeburg [all partners]
  • 08.05.2018 - Meeting at TU Chemnitz [TUCh, TUIl]
  • 07.05.2018 - Modelling workshop at ENSO NETZ GmbH in Dresden [MPI, TUIl, ENSO]
  • 02.05.2018 - Modelling workshop at Venios GmbH in Frankfurt am Main [MPI, TUIl, Venios]
  • 09.04.2018 - Kick-off meeting of all project partners involved at TU Chemnitz [all partners]

Page created by Manuel Baumann and maintained by Philipp Sauerteig, last updated: November 2021