@article{PoettgenEdererAltherretal.2015,
  author    = {P{\"o}ttgen, Philipp and Ederer, Thorsten and Altherr, Lena and Lorenz, Ulf and Pelz, Peter F.},
  title     = {Examination and optimization of a heating circuit for energy-efficient buildings},
  series = {Energy Technology},
  volume    = {4},
  journal   = {Energy Technology},
  number    = {1},
  publisher = {WILEY-VCH Verlag},
  address   = {Weinheim},
  isbn      = {2194-4296},
  doi       = {10.1002/ente.201500252},
  pages     = {136 -- 144},
  year      = {2015},
  abstract  = {The conference center darmstadtium in Darmstadt is a prominent example of energy efficient buildings. Its heating system consists of different source and consumer circuits connected by a Zortstr{\"o}m reservoir. Our goal was to reduce the energy costs of the system as much as possible. Therefore, we analyzed its supply circuits. The first step towards optimization is a complete examination of the system: 1) Compilation of an object list for the system, 2) collection of the characteristic curves of the components, and 3) measurement of the load profiles of the heat and volume-flow demand. Instead of modifying the system manually and testing the solution by simulation, the second step was the creation of a global optimization program. The objective was to minimize the total energy costs for one year. We compare two different topologies and show opportunities for significant savings.},
  language  = {en}
}
@article{AltherrEdererPoettgenetal.2015,
  author    = {Altherr, Lena and Ederer, Thorsten and P{\"o}ttgen, Philipp and Lorenz, Ulf and Pelz, Peter F.},
  title     = {Multicriterial optimization of technical systems considering multiple load and availability scenarios},
  series = {Applied Mechanics and Materials},
  volume    = {807},
  journal   = {Applied Mechanics and Materials},
  editor    = {Pelz, Peter F. and Groche, Peter},
  isbn      = {1660-9336},
  doi       = {10.4028/www.scientific.net/AMM.807.247},
  pages     = {247 -- 256},
  year      = {2015},
  abstract  = {Cheap does not imply cost-effective -- this is rule number one of zeitgeisty system design. The initial investment accounts only for a small portion of the lifecycle costs of a technical system. In fluid systems, about ninety percent of the total costs are caused by other factors like power consumption and maintenance. With modern optimization methods, it is already possible to plan an optimal technical system considering multiple objectives. In this paper, we focus on an often neglected contribution to the lifecycle costs: downtime costs due to spontaneous failures. Consequently, availability becomes an issue.},
  language  = {en}
}
@article{AltherrEdererLorenzetal.2014,
  author    = {Altherr, Lena and Ederer, Thorsten and Lorenz, Ulf and Pelz, Peter F. and P{\"o}ttgen, Philipp},
  title     = {Experimental validation of an enhanced system synthesis approach},
  series = {Operations Research Proceedings 2014},
  journal   = {Operations Research Proceedings 2014},
  editor    = {L{\"u}bbecke, Marco and Koster, Arie and Letmathe, Peter and Madlener, Reihard and Peis, Britta and Walther, Grit},
  publisher = {Springer},
  address   = {Basel},
  isbn      = {978-3-319-28695-2},
  doi       = {10.1007/978-3-319-28697-6_1},
  pages     = {6},
  year      = {2014},
  abstract  = {Planning the layout and operation of a technical system is a common task for an engineer. Typically, the workflow is divided into consecutive stages: First, the engineer designs the layout of the system, with the help of his experience or of heuristic methods. Secondly, he finds a control strategy which is often optimized by simulation. This usually results in a good operating of an unquestioned sys- tem topology. In contrast, we apply Operations Research (OR) methods to find a cost-optimal solution for both stages simultaneously via mixed integer program- ming (MILP). Technical Operations Research (TOR) allows one to find a provable global optimal solution within the model formulation. However, the modeling error due to the abstraction of physical reality remains unknown. We address this ubiq- uitous problem of OR methods by comparing our computational results with mea- surements in a test rig. For a practical test case we compute a topology and control strategy via MILP and verify that the objectives are met up to a deviation of 8.7\%.},
  language  = {en}
}