减压阀和节流阀在配水管网压力优化管理中的应用

IF 1.6 3区 环境科学与生态学 Q3 WATER RESOURCES Urban Water Journal Pub Date : 2023-10-04 DOI:10.1080/1573062x.2023.2263424
Niuosha Hedaiaty Marzouny, Mohammadreza Jalili Ghazizadeh, Iman Moslehi, Mahdi Komeily
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引用次数: 0

摘要

【摘要】先进的压力控制技术促进了配水管网的智能化管理。在本研究中,提出了一种基于优化的方法来制定基于时间的减压阀计划。为此,首先描述了一个单目标优化问题,寻求最小化节点压力的时空变化。然后,在两种情况下解决了prv的应用,即单独(即使用prv)和混合(即组合使用prv和节流阀控制阀[tcv])。所提出的情景随后被应用于合成和真实wdn的水力模型。进一步测量包括变异指数(VI)在内的一组水力评价指标,以确定最佳压力管理方案。研究结果表明,与单独工况相比,混合工况下的VI降低幅度更大,压力控制效率更高(合成wdn和真实wdn分别为39.9%和11.8%)。关键词:压力管理减压阀节流控制阀仿真优化模型遗传算法致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢致谢披露声明作者未报告潜在的利益冲突。数据的可获得性支持本研究结果的数据可根据合理要求从通讯作者(Jalili Ghazizadeh, M.)处获得。
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Application of pressure reducing and throttle control valves for optimal pressure management in water distribution networks
ABSTRACTAdvanced pressure control facilitates the smart management of water distribution networks (WDNs). In this study, an optimization-based method is proposed to develop a time-based schedule for pressure reducing valves (PRVs). For this purpose, a single-objective optimization problem is initially delineated, seeking to minimize spatiotemporal variations in the nodal pressures. Then, the application of PRVs is addressed in two scenarios, viz. individual (i.e. employing PRVs) and hybrid (i.e. the combined use of PRVs and throttle control valves [TCVs]). The proposed scenarios are subsequently applied to the hydraulic model of synthetic and real WDNs. A set of hydraulic evaluation indices, including variation index (VI), are further measured to spot the optimal pressure management scenario. The study results establish that the hybrid scenario leads to a larger decrease in the VI along with more efficient pressure control (namely, 39.9% and 11.8% in the synthetic and real WDNs, respectively), compared with the individual one.KEYWORDS: Pressure managementpressure reducing valvethrottle control valvesimulation-optimization modelGenetic algorithm AcknowledgementsThe authors would like to extend their appreciation to Mashhad Water and Wastewater Company for providing the required data associated with the water distribution network examined, which made this study possible.Disclosure statementNo potential conflict of interest was reported by the author(s).Availability of dataThe data that support the findings of this study are available from the corresponding author (Jalili Ghazizadeh, M.) upon reasonable request.
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来源期刊
Urban Water Journal
Urban Water Journal WATER RESOURCES-
CiteScore
4.40
自引率
11.10%
发文量
101
审稿时长
3 months
期刊介绍: Urban Water Journal provides a forum for the research and professional communities dealing with water systems in the urban environment, directly contributing to the furtherance of sustainable development. Particular emphasis is placed on the analysis of interrelationships and interactions between the individual water systems, urban water bodies and the wider environment. The Journal encourages the adoption of an integrated approach, and system''s thinking to solve the numerous problems associated with sustainable urban water management. Urban Water Journal focuses on the water-related infrastructure in the city: namely potable water supply, treatment and distribution; wastewater collection, treatment and management, and environmental return; storm drainage and urban flood management. Specific topics of interest include: network design, optimisation, management, operation and rehabilitation; novel treatment processes for water and wastewater, resource recovery, treatment plant design and optimisation as well as treatment plants as part of the integrated urban water system; demand management and water efficiency, water recycling and source control; stormwater management, urban flood risk quantification and management; monitoring, utilisation and management of urban water bodies including groundwater; water-sensitive planning and design (including analysis of interactions of the urban water cycle with city planning and green infrastructure); resilience of the urban water system, long term scenarios to manage uncertainty, system stress testing; data needs, smart metering and sensors, advanced data analytics for knowledge discovery, quantification and management of uncertainty, smart technologies for urban water systems; decision-support and informatic tools;...
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