期刊
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
卷 144, 期 7, 页码 -出版社
ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)WR.1943-5452.0000956
关键词
Water distribution system; Optimization; Pipe burst; Response; Intervention; Recovery; Hydraulic solver
资金
- Kurdistan Regional Government in Iraq, Ministry of High Education and Scientific Research, through the Human Capacity Development Program (HCDP)
This paper presents a methodology for developing efficient and effective operational, short-time response to an unplanned failure event (e.g.,a pipe burst or equipment failure) in a water distribution system (WDS). The proposed automated response methodology consists of isolating the failure event followed by the recovery of the affected system part by restoring the flows and pressures to normal conditions. The isolation is typically achieved by manipulating the nearby on/off valves. The recovery, which is the focus of this work, involves selecting an optimal combination of suitable operational interventions from a number of possible choices with the aim to reduce the negative impact of the failure (e.g.,volume of water undelivered to consumers) over a prespecified time horizon. The intervention options considered here include valve manipulations, changing the pressure reducing valve's (PRV) outlet pressure, and installation and use of temporary overland bypasses from nearby hydrants in an adjacent, unaffected part of the network. The optimal mix of interventions is identified by using a multiobjective optimization approach driven by the minimization of the negative impact on the consumers and the minimization of the corresponding number of operational interventions (which acts as a surrogate for operational costs). This methodology has been applied to a real-world water distribution network of C-Town. The results obtained demonstrate the effectiveness of the proposed methodology in identifying the Pareto optimal intervention strategies that could be ultimately presented to the control room operator for making a suitable decision in near real time.
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