Optimizing booster stations

Weber, Jonas B.; Lorenz, Ulf

doi:10.1145/3067695.3082482

Cited by 10 publications

(9 citation statements)

References 7 publications

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“…In this context, another measure would be to limit the temperature observation to thermal components only. For solving the problem efficiently, we plan to adopt the approach for fluid systems suggested in [9] which uses specified primal and dual solution techniques at the same time. Furthermore, we introduced a continuous time-representation for technical fluid-based systems.…”

Section: Discussionmentioning

confidence: 99%

“…Since thermofluid systems are an extension of fluid systems, we shortly introduce the relevant constraints for the quasi-stationary case. For a more detailed view of the underlying logical, physical and technical properties, we refer to [9]. An overview of all variables and parameters used is given in Table 1.…”

Section: Basic Network Model For Fluid Systemsmentioning

confidence: 99%

“…Furthermore, Pöttgen et al [7] compared linear and non-linear programming techniques for the combined layout and control optimization of booster stations, while favorable combinations between model formulations and mathematical solver packages have been studied in [8]. In addition to standard solver packages, problem specific primal and dual solution algorithms for the linear formulation have been developed in [9] to speed up the solution process.…”

Section: Introductionmentioning

confidence: 99%

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Algorithmic System Design of Thermofluid Systems

Weber

Lorenz

2018

EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization

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Technical components are usually well optimized. However, simply combining these optimized components in a technical system does not necessarily lead to optimal systems. Therefore, focusing on a system perspective reveals new potential for optimization. In this context, we examine thermofluid systems which can be interpreted as fluid systems with superimposed heat transfer. The structure of such systems can be abstracted as a graph -more specifically, a flow network. We translate the underlying optimization problem into a mixed-integer linear program which is designed to obey the physical laws of heat transfer. Typically, fluid systems can be considered as quasi-stationary systems since their dynamic effects are usually negligible. However, for thermofluid systems this assumption does not hold because time-dependency is an issue as storage tanks for heated fluid gain importance. In order to handle the dynamic effects induced by the storage tanks, we further introduce a continuous-time representation based on a global event-based formulation.

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Section: Discussionmentioning

confidence: 99%

Section: Basic Network Model For Fluid Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Algorithmic System Design of Thermofluid Systems

Weber

Lorenz

2018

EngOpt 2018 Proceedings of the 6th International Conference on Engineering Optimization

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“…In this spirit, [10] used a non-linear model formulation to design decentralized water supply systems for skyscrapers. In addition to generic solver packages, problem specific primal and dual solution algorithms for the linear formulation were developed in [11] to speed up the solution process. In an attempt to generate robust control strategies for uncertain loads, [12] introduced a robust but energy-efficient activation strategy for switching between the operating and non-operating pumps of booster stations.…”

Section: Introductionmentioning

confidence: 99%

“…is outlined in (11) and (12) and is modeled using the linearization technique presented in [24]. As the power consumption of the booster station in the case of a breakdown is not subject of the optimization the non-linear relation between h B p and q B p can be modeled more easily: (13) ensures that the selected operating point (h B p , q B p ) lies somewhere within the characteristic map without specifying the speed of the pump.…”

mentioning

confidence: 99%

Towards Resilient Process Networks - Designing Booster Stations via Quantified Programming

Hartisch

Herbst

Lorenz

et al. 2018

AMM

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Resilience of a technical system is the ability to overcome minor failures and thus to avoid a complete breakdown of its vital functions. A possible failure of the system's components is one critical case the system designer should keep in mind. From another perspective resilience can be interpreted as the existence of alternative paths in a process network if resources break down. In this context we deal with process networks corresponding to systems which must be designed to operate in different scenarios. In order to ensure the system's functionality and to step in as a replacement in case of failure a set of optional resources must be available. This means that the process network must have several degrees of freedom allowing to react to uncertain events. With those restrictions we try to find a preferably resource-efficient network. Hence, an optimization problem arises which can be modeled using quantified mixed-integer linear programming. As an example of a process which can be modeled using process networks we investigate the problem of finding cost-efficient resilient topologies of fluid systems that are able to fulfill different load scenarios.

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