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首页> 外文期刊>Journal of Water Resources Planning and Management >Maximizing Hydropower Generation in Gravity Water Distribution Networks: Determining the Optimal Location and Number of Pumps as Turbines
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Maximizing Hydropower Generation in Gravity Water Distribution Networks: Determining the Optimal Location and Number of Pumps as Turbines

机译:最大化重力自来水网络中的水力发电:确定作为涡轮机的泵的最佳位置和数量

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摘要

Water distribution networks have to face the challenge of providing for a growing population with efficient management of water and energy. Pressure control in water networks is an efficient strategy to reduce leakage, which is usually carried out by installing pressure-reducing valves. Because the operation of these elements involves energy dissipation, the replacement of pressure-reducing valves by hydropower turbines has been widely analyzed. Thus, in this work a methodology focused on the detection of the optimal location and number of pumps as turbines (PATs) to maximize hydropower generation in gravity water distribution networks is proposed. The methodology considers a mathematical optimization and evaluates the real PAT performance at each node. Installation costs and payback period have been considered to determine the viability of installations. The application of this methodology to six water distribution networks showed potential hydropower locations in three, with values of daily recovered energy from 43 to 231 kWh. Although the optimization methodology developed here is not suitable for complex looped networks due to the computational time required, for branched networks it is a powerful tool offering decision makers information about hourly power, total installation costs, and payback period at each potential node in a network.
机译:供水网络必须面对为不断增长的人口提供有效的水和能源管理的挑战。水网络中的压力控制是减少泄漏的有效策略,通常可通过安装减压阀来实现。由于这些元件的运行涉及能量耗散,因此对水力涡轮机替代减压阀进行了广泛的分析。因此,在这项工作中,提出了一种方法,该方法侧重于检测作为涡轮机(PAT)的泵的最佳位置和数量,以使重力水分配网络中的水力发电最大化。该方法考虑了数学优化,并评估了每个节点的实际PAT性能。已考虑安装成本和投资回收期,以确定安装的可行性。该方法在六个供水网络中的应用显示了三个潜在的水电位置,每天回收的能量值从43到231千瓦时。尽管此处开发的优化方法由于所需的计算时间而不适用于复杂的环形网络,但对于分支网络而言,它是功能强大的工具,可为决策者提供有关网络中每个潜在节点的小时电量,总安装成本和投资回收期的信息。

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