农业智能水管理:重力配水系统最优调度方案的建议

V. Latorre, L. Zingali, C. Bragalli, A. Domeneghetti, A. Brath
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引用次数: 2

摘要

农业是用水需求最大的部门之一,在制定节水政策方面发挥着核心作用。在本文中,我们提出了一种改进的方法来解决灌溉调度问题,减少水的浪费,同时满足农民和作物的用水需求。对于按需分配方式管理的配水系统,灌溉的效率取决于网络管理员(即看门人)保证适当服务的能力,包括:灌溉调度,在给定时间内通过渠道的水量的定义,以及闸门和水闸的操作,使水到达农场。因此,灌溉调度的低效率可能受到以下方面的限制:1)减少水的浪费,2)最小化看门人的工作,3)最大化满足农民的需求。我们提出了一个改进的混合整数线性优化公式,增加了在通道中储存水的可能性,并考虑了渗流。这种新公式能够更好地表示水道网络中水流的物理行为,也避免了洪水的存在。提出的优化解决方案嵌入在一个更广泛的监测框架中,目的是充分利用安装在现场的模型、存储库和传感器的复杂网络的可用性。得到的问题由最常用的优化求解器之一(IBM ILOG Cplex)解决,并在合成基准测试中进行了测试。此外,我们在网络的数字副本上验证了结果,该网络执行灌溉系统的水力模拟。如果系统中引入的水能够满足农民的要求,并且经过考虑的时间不会产生洪水,则该调度被接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart Water Management in Agriculture: a Proposal for an Optimal Scheduling Formulation of a Gravity Water Distribution System
Agriculture represents one of the most water demanding sectors and its role is central on defining water saving policies. In this work, we propose an improved approach to the irrigation scheduling problem, reducing water wastage while satisfying farmers’ demands and crops’ water needs.For water distribution system managed with on-demand distribution approach, the efficiency of irrigation relies on the ability of the network manager (i.e., gatekeeper) to guarantee a proper service, consisting in: the irrigation scheduling, the definition of the volume of water passing through the channels at a given time, and the operations on gates and sluices to make the water reach the farms. Consequently, the irrigation scheduling inefficiencies might be limited by: i) reducing the water wastage, ii) minimizing the gatekeeper work and iii) maximizing the satisfaction of the farmers’ requirements.We propose an improved mixed-integer linear optimization formulation that adds the possibility to store water in the channels and takes seepage into account. This new formulation is able to better represent the physical behavior of the water flow in the channels network, also avoiding the presence of flooding. The proposed optimization solution is embedded within a wider monitoring framework with the intent to fully exploit the availability of a complex network of models, repositories and sensors installed in the field.The resulting problem is solved by one of the most used optimization solvers (IBM ILOG Cplex) and tested on a synthetic benchmark. Furthermore, we validate the results on a digital copy of the network that performs a hydraulic simulation of the irrigation system. The scheduling is accepted if the water introduced in the system can satisfy farmers’ requests with the considered timing and does not produce flooding.
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