@inproceedings{LeiseAltherr2018,
  author    = {Leise, Philipp and Altherr, Lena},
  title     = {Optimizing the design and control of decentralized water supply systems - a case-study of a hotel building},
  series = {EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization},
  booktitle = {EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-319-97773-7},
  doi       = {10.1007/978-3-319-97773-7_107},
  pages     = {1241 -- 1252},
  year      = {2018},
  abstract  = {To increase pressure to supply all floors of high buildings with water, booster stations, normally consisting of several parallel pumps in the basement, are used. In this work, we demonstrate the potential of a decentralized pump topology regarding energy savings in water supply systems of skyscrapers. We present an approach, based on Mixed-Integer Nonlinear Programming, that allows to choose an optimal network topology and optimal pumps from a predefined construction kit comprising different pump types. Using domain-specific scaling laws and Latin Hypercube Sampling, we generate different input sets of pump types and compare their impact on the efficiency and cost of the total system design. As a realistic application example, we consider a hotel building with 325 rooms, 12 floors and up to four pressure zones.},
  language  = {en}
}
@article{SunAltherrPeietal.2018,
  author    = {Sun, Hui and Altherr, Lena and Pei, Ji and Pelz, Peter F. and Yuan, Shouqi},
  title     = {Optimal booster station design and operation under uncertain load},
  series = {Applied Mechanics and Materials},
  volume    = {885},
  journal   = {Applied Mechanics and Materials},
  publisher = {Trans Tech Publications},
  address   = {B{\"a}ch},
  issn      = {1662-7482},
  doi       = {10.4028/www.scientific.net/AMM.885.102},
  pages     = {102 -- 115},
  year      = {2018},
  abstract  = {Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the system's resilience can be engineered},
  language  = {en}
}