@inproceedings{LeiseBreuerAltherretal.2020,
  author    = {Leise, Philipp and Breuer, Tim and Altherr, Lena and Pelz, Peter F.},
  title     = {Development, validation and assessment of a resilient pumping system},
  series = {Proceedings of the Joint International Resilience Conference, JIRC2020},
  booktitle = {Proceedings of the Joint International Resilience Conference, JIRC2020},
  isbn      = {978-90-365-5095-6},
  pages     = {97 -- 100},
  year      = {2020},
  abstract  = {The development of resilient technical systems is a challenging task, as the system should adapt automatically to unknown disturbances and component failures. To evaluate different approaches for deriving resilient technical system designs, we developed a modular test rig that is based on a pumping system. On the basis of this example system, we present metrics to quantify resilience and an algorithmic approach to improve resilience. This approach enables the pumping system to automatically react on unknown disturbances and to reduce the impact of component failures. In this case, the system is able to automatically adapt its topology by activating additional valves. This enables the system to still reach a minimum performance, even in case of failures. Furthermore, timedependent disturbances are evaluated continuously, deviations from the original state are automatically detected and anticipated in the future. This allows to reduce the impact of future disturbances and leads to a more resilient system behaviour.},
  language  = {en}
}
@inproceedings{LeiseSimonAltherr2020,
  author    = {Leise, Philipp and Simon, Nicolai and Altherr, Lena},
  title     = {Comparison of Piecewise Linearization Techniques to Model Electric Motor Efficiency Maps: A Computational Study},
  series = {Operations Research Proceedings 2019},
  booktitle = {Operations Research Proceedings 2019},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-48439-2},
  doi       = {10.1007/978-3-030-48439-2_55},
  pages     = {457 -- 463},
  year      = {2020},
  abstract  = {To maximize the travel distances of battery electric vehicles such as cars or buses for a given amount of stored energy, their powertrains are optimized energetically. One key part within optimization models for electric powertrains is the efficiency map of the electric motor. The underlying function is usually highly nonlinear and nonconvex and leads to major challenges within a global optimization process. To enable faster solution times, one possibility is the usage of piecewise linearization techniques to approximate the nonlinear efficiency map with linear constraints. Therefore, we evaluate the influence of different piecewise linearization modeling techniques on the overall solution process and compare the solution time and accuracy for methods with and without explicitly used binary variables.},
  language  = {en}
}
@inproceedings{MuellerAltherrLeiseetal.2020,
  author    = {M{\"u}ller, Tim M. and Altherr, Lena and Leise, Philipp and Pelz, Peter F.},
  title     = {Optimization of pumping systems for buildings: Experimental validation of different degrees of model detail on a modular test rig},
  series = {Operations Research Proceedings 2019},
  booktitle = {Operations Research Proceedings 2019},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-48438-5},
  doi       = {10.1007/978-3-030-48439-2_58},
  pages     = {481 -- 488},
  year      = {2020},
  abstract  = {Successful optimization requires an appropriate model of the system under consideration. When selecting a suitable level of detail, one has to consider solution quality as well as the computational and implementation effort. In this paper, we present a MINLP for a pumping system for the drinking water supply of high-rise buildings. We investigate the influence of the granularity of the underlying physical models on the solution quality. Therefore, we model the system with a varying level of detail regarding the friction losses, and conduct an experimental validation of our model on a modular test rig. Furthermore, we investigate the computational effort and show that it can be reduced by the integration of domain-specific knowledge.},
  language  = {en}
}