TY  - CHAP
A1  - Altherr, Lena
A1  - Ederer, Thorsten
A1  - Schänzle, Christian
A1  - Lorenz, Ulf
A1  - Pelz, Peter F.
T1  - Algorithmic system design using scaling and affinity laws
T2  - Operations Research Proceedings 2015
N2  - Energy-efficient components do not automatically lead to energy-efficient systems. Technical Operations Research (TOR) shifts the focus from the single component to the system as a whole and finds its optimal topology and operating strategy simultaneously. In previous works, we provided a preselected construction kit of suitable components for the algorithm. This approach may give rise to a combinatorial explosion if the preselection cannot be cut down to a reasonable number by human intuition. To reduce the number of discrete decisions, we integrate laws derived from similarity theory into the optimization model. Since the physical characteristics of a production series are similar, it can be described by affinity and scaling laws. Making use of these laws, our construction kit can be modeled more efficiently: Instead of a preselection of components, it now encompasses whole model ranges. This allows us to significantly increase the number of possible set-ups in our model. In this paper, we present how to embed this new formulation into a mixed-integer program and assess the run time via benchmarks. We present our approach on the example of a ventilation system design problem.
KW  - Optimal Topology
KW  - Piecewise Linearization
KW  - Ventilation System
KW  - Similarity Theory
Y1  - 2017
SN  - 978-3-319-42901-4
SN  - 978-3-319-42902-1
U6  - http://dx.doi.org/10.1007/978-3-319-42902-1
N1  - International Conference of the German, Austrian and Swiss Operations Research Societies (GOR, ÖGOR, SVOR/ASRO), University of Vienna, Austria, September 1-4, 2015
SP  - 605
EP  - 611
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Schänzle, Christian
A1  - Altherr, Lena
A1  - Ederer, Thorsten
A1  - Lorenz, Ulf
A1  - Pelz, Peter F.
T1  - As good as it can be: Ventilation system design by a combined scaling and discrete optimization method
T2  - Proceedings of FAN 2015
N2  - The understanding that optimized components do not automatically lead to energy-efficient systems sets the attention from the single component on the entire technical system. At TU Darmstadt, a new field of research named Technical Operations Research (TOR) has its origin. It combines mathematical and technical know-how for the optimal design of technical systems. We illustrate our optimization approach in a case study for the design of a ventilation system with the ambition to minimize the energy consumption for a temporal distribution of diverse load demands. By combining scaling laws with our optimization methods we find the optimal combination of fans and show the advantage of the use of multiple fans.
Y1  - 2015
N1  - Proceedings of FAN 2015, Lyon (France), 15 – 17 April 2015
SP  - 1
EP  - 11
ER  - 
TY  - CHAP
A1  - Schänzle, Christian
A1  - Altherr, Lena
A1  - Ederer, Thorsten
A1  - Pelz, Peter
T1  - TOR – Towards the energetically optimal ventilation system
KW  - Energy
KW  - Efficiency
KW  - Ventilation System
KW  - Discrete Optimisation
KW  - TGA
Y1  - 2015
N1  - EST 2015, Karlsruhe, 19-21 Mai 2015
ER  -