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    Topological State Estimation in Water Distribution Systems: Mixed-Integer Quadratic Programming Approach

    Source: Journal of Water Resources Planning and Management:;2018:;Volume ( 144 ):;issue: 007
    Author:
    Díaz Sarai;Mínguez Roberto;González Javier
    DOI: 10.1061/(ASCE)WR.1943-5452.0000934
    Publisher: American Society of Civil Engineers
    Abstract: State estimation (SE) techniques can be applied to compute the most likely hydraulic state of a water distribution system from the available measurements at a given time. Different approaches exist in the technical literature to undertake such an analysis, but in all of them it is assumed that pump and valve statuses are known beforehand. Such consideration may lead to unrealistic results if real-time unnotified changes in the operation of the network take place, limiting the usefulness of the information provided by telemetry systems. This work eliminates the known-status assumption and presents the concept of topological state estimation (TSE), which not only computes the hydraulic state of the system, but also the current pump and valve status according to the existing measurements. More specifically, a novel methodology for TSE is set out in this paper. The proposed method is derived from the original mixed-integer non-linear programming formulation of the problem, which is transformed in an iterative mixed-integer quadratic programming problem by linearizing some hydraulic constraints. The potential of the methodology is presented by means of an illustrative example and a large case study, in which pumps, gate valves and check valves exist. Results show that TSE would successfully contribute to make the most of available telemetry systems, hence expanding the online monitoring possibilities of water distribution networks.
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      Topological State Estimation in Water Distribution Systems: Mixed-Integer Quadratic Programming Approach

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    contributor authorDíaz Sarai;Mínguez Roberto;González Javier
    date accessioned2019-02-26T07:35:38Z
    date available2019-02-26T07:35:38Z
    date issued2018
    identifier other%28ASCE%29WR.1943-5452.0000934.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4248128
    description abstractState estimation (SE) techniques can be applied to compute the most likely hydraulic state of a water distribution system from the available measurements at a given time. Different approaches exist in the technical literature to undertake such an analysis, but in all of them it is assumed that pump and valve statuses are known beforehand. Such consideration may lead to unrealistic results if real-time unnotified changes in the operation of the network take place, limiting the usefulness of the information provided by telemetry systems. This work eliminates the known-status assumption and presents the concept of topological state estimation (TSE), which not only computes the hydraulic state of the system, but also the current pump and valve status according to the existing measurements. More specifically, a novel methodology for TSE is set out in this paper. The proposed method is derived from the original mixed-integer non-linear programming formulation of the problem, which is transformed in an iterative mixed-integer quadratic programming problem by linearizing some hydraulic constraints. The potential of the methodology is presented by means of an illustrative example and a large case study, in which pumps, gate valves and check valves exist. Results show that TSE would successfully contribute to make the most of available telemetry systems, hence expanding the online monitoring possibilities of water distribution networks.
    publisherAmerican Society of Civil Engineers
    titleTopological State Estimation in Water Distribution Systems: Mixed-Integer Quadratic Programming Approach
    typeJournal Paper
    journal volume144
    journal issue7
    journal titleJournal of Water Resources Planning and Management
    identifier doi10.1061/(ASCE)WR.1943-5452.0000934
    page4018026
    treeJournal of Water Resources Planning and Management:;2018:;Volume ( 144 ):;issue: 007
    contenttypeFulltext
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