research-article

Optimizing booster stations

Authors:

Jonas B. Weber,

Ulf LorenzAuthors Info & Claims

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

Pages 1303 - 1310

https://doi.org/10.1145/3067695.3082482

Published: 15 July 2017 Publication History

Abstract

Booster stations are fluid systems consisting of interconnected components such as pumps, pipes, valves and fittings. One of their main applications is to supply whole buildings or higher floors with drinking water if the supply pressure of the water company is not high enough to guarantee a continuous supply for all consumers. This means that a booster station must increase the pressure of supplied drinking water at a given time-variant flow rate. The consumer's demands must be matched at any time and the system operation is restricted by the general laws of fluid mechanics.

A common approach to handle the corresponding optimization problem is to model it as a mixed integer linear program (MILP) and to solve this program using a standard MILP solver. This approach is not suitable for large problem instances with practical relevance as it is not possible to obtain good solutions in reasonable time. Hence, the main obstacle is the optimization speed.

In this work, we present an approach to obtain good solutions in reasonable time even for large practical relevant instances. We do this by addressing the problem with heuristics from both the primal and dual side combined with the use of problem specific and technical knowledge. This approach is based on modeling the problem as a MILP as well as a mathematical graph and using both views simultaneously.

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Digital Library

Cited By

Gutiérrez-Bahamondes JMora-Melia DValdivia-Muñoz BSilva-Aravena FIglesias-Rey P(2023)Infeasibility Maps: Application to the Optimization of the Design of Pumping Stations in Water Distribution NetworksMathematics10.3390/math1107158211:7(1582)Online publication date: 24-Mar-2023
https://doi.org/10.3390/math11071582
Gan XPei JPavesi GYuan SWang W(2022)Application of intelligent methods in energy efficiency enhancement of pump system: A reviewEnergy Reports10.1016/j.egyr.2022.09.0168(11592-11606)Online publication date: Nov-2022
https://doi.org/10.1016/j.egyr.2022.09.016
Weber JHartisch MHerbst ALorenz U(2020)Towards an algorithmic synthesis of thermofluid systemsOptimization and Engineering10.1007/s11081-020-09564-1Online publication date: 18-Sep-2020
https://doi.org/10.1007/s11081-020-09564-1
Show More Cited By

Index Terms

Optimizing booster stations
1. Applied computing
  1. Operations research
  2. Physical sciences and engineering
    1. Engineering
      1. Computer-aided design
2. Mathematics of computing
  1. Discrete mathematics
    1. Combinatorics
      1. Combinatorial optimization
    2. Graph theory
      1. Network flows

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cover image ACM Conferences

GECCO '17: Proceedings of the Genetic and Evolutionary Computation Conference Companion

July 2017

1934 pages

ISBN:9781450349390

DOI:10.1145/3067695

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 15 July 2017

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GECCO '17: Genetic and Evolutionary Computation Conference

July 15 - 19, 2017

Berlin, Germany

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Gutiérrez-Bahamondes JMora-Melia DValdivia-Muñoz BSilva-Aravena FIglesias-Rey P(2023)Infeasibility Maps: Application to the Optimization of the Design of Pumping Stations in Water Distribution NetworksMathematics10.3390/math1107158211:7(1582)Online publication date: 24-Mar-2023
https://doi.org/10.3390/math11071582
Gan XPei JPavesi GYuan SWang W(2022)Application of intelligent methods in energy efficiency enhancement of pump system: A reviewEnergy Reports10.1016/j.egyr.2022.09.0168(11592-11606)Online publication date: Nov-2022
https://doi.org/10.1016/j.egyr.2022.09.016
Weber JHartisch MHerbst ALorenz U(2020)Towards an algorithmic synthesis of thermofluid systemsOptimization and Engineering10.1007/s11081-020-09564-1Online publication date: 18-Sep-2020
https://doi.org/10.1007/s11081-020-09564-1
Müller TLeise PLorenz IAltherr LPelz P(2020)Optimization and validation of pumping system design and operation for water supply in high-rise buildingsOptimization and Engineering10.1007/s11081-020-09553-422:2(643-686)Online publication date: 19-Sep-2020
https://doi.org/10.1007/s11081-020-09553-4
Müller TAltherr LLeise PPelz P(2020)Optimization of Pumping Systems for Buildings: Experimental Validation of Different Degrees of Model Detail on a Modular Test RigOperations Research Proceedings 201910.1007/978-3-030-48439-2_58(481-488)Online publication date: 25-Sep-2020
https://doi.org/10.1007/978-3-030-48439-2_58
Weber JHartisch MLorenz U(2020)Optimized Design of Thermofluid Systems Using the Example of Mold Cooling in Injection MoldingOperations Research Proceedings 201910.1007/978-3-030-48439-2_57(473-480)Online publication date: 25-Sep-2020
https://doi.org/10.1007/978-3-030-48439-2_57
Altherr LLeise PPfetsch MSchmitt A(2018)Algorithmic Design and Resilience Assessment of Energy Efficient High-Rise Water Supply SystemsApplied Mechanics and Materials10.4028/www.scientific.net/AMM.885.211885(211-223)Online publication date: Nov-2018
https://doi.org/10.4028/www.scientific.net/AMM.885.211
Hartisch MHerbst ALorenz UWeber J(2018)Towards Resilient Process Networks - Designing Booster Stations via Quantified ProgrammingApplied Mechanics and Materials10.4028/www.scientific.net/AMM.885.199885(199-210)Online publication date: Nov-2018
https://doi.org/10.4028/www.scientific.net/AMM.885.199
Weber JLorenz U(2018)Algorithmic System Design of Thermofluid SystemsEngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization10.1007/978-3-319-97773-7_13(132-143)Online publication date: 14-Sep-2018
https://doi.org/10.1007/978-3-319-97773-7_13

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