@article{MuellerLeiseLorenzetal.2020,
  author    = {M{\"u}ller, Tim M. and Leise, Philipp and Lorenz, Imke-Sophie and Altherr, Lena and Pelz, Peter F.},
  title     = {Optimization and validation of pumping system design and operation for water supply in high-rise buildings},
  series = {Optimization and Engineering},
  volume    = {2021},
  journal   = {Optimization and Engineering},
  number    = {22},
  publisher = {Springer},
  issn      = {1573-2924},
  doi       = {10.1007/s11081-020-09553-4},
  pages     = {643 -- 686},
  year      = {2020},
  abstract  = {The application of mathematical optimization methods for water supply system design and operation provides the capacity to increase the energy efficiency and to lower the investment costs considerably. We present a system approach for the optimal design and operation of pumping systems in real-world high-rise buildings that is based on the usage of mixed-integer nonlinear and mixed-integer linear modeling approaches. In addition, we consider different booster station topologies, i.e. parallel and series-parallel central booster stations as well as decentral booster stations. To confirm the validity of the underlying optimization models with real-world system behavior, we additionally present validation results based on experiments conducted on a modularly constructed pumping test rig. Within the models we consider layout and control decisions for different load scenarios, leading to a Deterministic Equivalent of a two-stage stochastic optimization program. We use a piecewise linearization as well as a piecewise relaxation of the pumps' characteristics to derive mixed-integer linear models. Besides the solution with off-the-shelf solvers, we present a problem specific exact solving algorithm to improve the computation time. Focusing on the efficient exploration of the solution space, we divide the problem into smaller subproblems, which partly can be cut off in the solution process. Furthermore, we discuss the performance and applicability of the solution approaches for real buildings and analyze the technical aspects of the solutions from an engineer's point of view, keeping in mind the economically important trade-off between investment and operation costs.},
  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}
}
@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}
}