Modeling and optimization of production and distribution of drinking water at VMW

We develop and discuss an operational planning model aiming at minimizing production and distribution costs in large drinking water networks containing buffers with free inflow. Modeling drinking water networks is very challenging due of the presence of complex hydraulic constraints, such as friction losses and pump curves. Non-linear, non-convex constraints result from the relationships between pressure and flow in power terms. Also, binary variables are needed to model the possibility of free inflow or re-injection of water at reservoirs. The resulting model is thus a non-convex Mixed-Integer Non-Linear Program (MINLP). A discrete-time setting is proposed to solve the problem over a finite horizon made of several intervals. A commercial solver, BONMIN, suited for convex MINLP models is used to heuristically solve the problem. We are able to find a good solution for a small part of an existing network operated by the Vlaamse Maatschappij voor Watervoorziening (VMW), a major drinking water company in Flanders

WaterBox: A Testbed for Monitoring and Controlling Smart Water Networks

Copyright 2015 ACM.Smart water distribution networks are a good example of a large scale Cyber-Physical System that requires monitoring for precise data analysis and network control. Due to the critical nature of water distribution, an extensive simulation of decision making and control algorithms are required before their deployment. Although some aspects of water network behaviour can be simulated in software such as hydraulic responses in valve changes, software simulators are unable to include dynamic events such as leakages or bursts in physical models. Furthermore, due to safety concerns, contemporary large-scale testbeds are limited to the monitoring processes or control methods with well established safety guarantees. Sophisticated algorithms for dynamic and optimal water network reconfiguration are not yet widespread. This paper presents a small-scale testbed, WaterBox, which allows the simulation of emerging/advanced monitoring and control algorithms in a fail-safe environment. The flexible hydraulic, hardware, and software infrastructure enables a substantial number of experiments. On-going experiments are related to in-node data processing and decision making, energy optimization, event-driven communication, and automatic control

Energy and Utilities Infrastructure: Can All be in One?

In today‘s developed society it is fully expected that every household is provided with general utility products such as heating, lighting, water supply, communication, and waste removal. Provision of these utility products requires large and complex physical, economic and social structures that interact and are interdependent. Furthermore, we underline that each distinct utility product (communication, transportation, water, etc.) provided to our households incurs similar material and embodied energy expenses. But are such structures and their respective expenses really necessary? Or could energy (and other resources) be saved by reducing redundant utility infrastructures, while still maintaining services to the households? Conventional approaches to improved utility provision focus on better management models with optimization, enhanced handling, and increased efficiency in organisations. This paper, on the other hand, presents a novel and radical idea to address this complex problem, by moving from the management level to the scientific & technological level. The paper challenges the need for distinct utility infrastructures for household utility products provision. In particular, the paper discusses the emerging scientific and technological options for using a single energy-provision infrastructure, which would potentially deliver the full set of household utility services

Real Data Analysis and Efficiency of the TEA Mantova Casale (Italy) Variable-speed Pumping Station

AbstractVariable speed pumps (VSPs) are widely used in water distribution systems (WDSs). They can increase the efficiency of the system and reduce the energy consumptions, when the functioning conditions move away from those used for the design. Affinity laws allow to model the characteristic curve of VSPs, in terms of dimensionless flow, head and power. Efficiency of the VSPs can also be predicted, although the effects of the variation in the rotation speed can be questioned. In this paper, the experimental data acquired by TeaAcque at the Mantova Casale pumping station are interpreted by means of the dimensionless equations derived by the affinity laws. The measured “wire to water” efficiency of the system is compared to the theoretical one

Water demand forecasting accuracy and influencing factors at different spatial scales using a Gradient Boosting Machine

Understanding, comparing, and accurately predicting water demand at different spatial scales is an important goal that will allow effective targeting of the appropriate operational and conservation efforts under an uncertain future. This study uses data relating to water consumption available at the household level, as well as postcode locations, household characteristics, and weather data in order to identify the relationships between spatial scale, influencing factors, and forecasting accuracy. For this purpose, a Gradient Boosting Machine (GBM) is used to predict water demand 1–7 days into the future. Results show an exponential decay in prediction accuracy from a Mean Absolute Percentage Error (MAPE) of 3.2% to 17%, for a reduction in group size from 600 to 5 households. Adding explanatory variables to the forecasting model reduces the MAPE up to 20% for the peak days and smaller household groups (20–56 households), whereas for larger aggregations of properties (100–804 households), the range of improvement is much smaller (up to 1.2%). Results also show that certain types of input variables (past consumption and household characteristics) become more important for smaller aggregations of properties, whereas others (weather data) become less important.Sanitary Engineerin

Computing and control for the water industry (CCWI2015)

PublishedWith rapid population growth, water withdrawals have tripled over the last 50 years and are predicted to increase by 50% by 2025 and may lead to an estimated 40% supply shortage. Water resources protection and improvements in their management are prime concerns for the water industry, which has to consider population increase and uncertainty of precipitation (extreme events such as drought and flood) due to climate change

Topological and Hydraulic Metrics-Based Search Space Reduction for Optimal Re-Sizing of Water Distribution Networks

The file attached to this record is the author's final peer reviewed version.Pipe re-sizing of Water Distribution Networks (WDNs) aims at improving the service performance to the required level, while minimizing the cost of replacing pipes in the network. The main challenge comes from the identification of the most effective pipes to re-size from a large number of interacting components. Performing a global search over all pipes in large WDNs does not guarantee to obtain a feasible and efficient solution due to the enormous search space, even by employing advanced algorithms, e.g., evolutionary algorithms. This paper proposes a novel method to reduce the search space for optimal re-sizing based on topological metrics from Complex Network Theory and hydraulic metrics, while providing sub-optimal solutions comparable to the full search solutions, i.e., considering all pipes as candidates. The topological metrics are based on the edge-betweenness tailored for WDN analysis. Hydraulic metrics are unit headloss and flow rates of pipes computed based on simulation of the WDN in the current configuration. The optimal re-sizing plans obtained, particularly that using edge betweenness were tested on a real WDN. The results are comparable with the full search solutions but they are much more efficient to obtain and require replacing mostly contiguous pipes, i.e., easier for practical fieldwork