Water distribution networks are large complex systems that are affected by leaks, which often entail high costs and may severely jeopardise the overall water distribution performance. Successful leak location 1 is paramount in order to minimize the impact of these leaks when occurring. Sensor placement is a key issue in the leak location 2 process, since the overall performance and success of this process highly depends on the choice of the sensors gathering data from the network. Common problems when isolating leaks in large scale highly-gridded real water distribution networks include leak mislabelling and large location areas obtention due to similarity of leak effect in the measurements, which may be caused by topological issues and led to incomplete coverage of the whole network. The sensor placement strategy may minimize these undesired effects by setting the sensor placement optimisation problem with the appropriate assumptions (e.g. geographically cluster alike leak behaviors) and taking into account real aspects of the practical application such as the acceptable leak location distance. In this paper, a sensor placement methodology considering these aspects and a general sensor distribution assessment method for leak diagnosis in water distribution systems is presented and exemplified with a small illustrative case study. Finally, the proposed method is applied to two real District Metered Areas (DMAs) located within the Barcelona water distribution network.
In this paper, a sensor data validation/reconstruction methodology applicable to water networks and its implementation by means of a software tool, are presented. The aim is to guarantee that the sensor data are reliable and complete in case that sensor faults occur. The availability of such dataset is of paramount importance in order to successfully use the sensor data for further tasks e.g. water billing, network efficiency assessment, leak localisation and real-time operational control. The methodology presented here is based on a sequence of tests and on the combined use of spatial models (SM) and time series models (TSM) applied to the sensors used for real-time monitoring and control of the water network. Spatial models take advantage of the physical relations between different system variables (e.g. flow and level sensors in hydraulic systems) while time series models take advantage of the temporal redundancy of the measured variables (here by means of a Holt-Winters (HW) time series model). First, the data validation approach, based on several tests of different complexity, is described to detect potential invalid or missing data. Then, the reconstruction process is based on a set of spatial and time series models used to reconstruct the missing/invalid data with the model estimation providing the best fit. A software tool implementing the proposed data validation and reconstruction methodology is also described. Finally, results obtained applying the proposed methodology to a real case study based on the Catalonia regional water network is used to illustrate its performance.
The efficient use of water resources is a subject of major concern for water utilities and authorities. One of the main challenges in improving the efficiency of drinking water networks is to minimize water loss in pipes due to leakage. Water leaks in water distribution networks (WDN) are unavoidable. They can cause significant economic losses in fluid transportation and an increase on reparation costs that finally generate an extra cost for the final consumer due to the waste of energy and chemicals in water treatment plants. It may also damage infrastructure and cause third party damage and health risks. In many WDN, losses due to leakage are estimated to account up to 30% of the total amount of extracted water; a very important issue in a world struggling to satisfy water demands of a growing population.Telemetry systems have long been used in large water distribution systems for improving real-time monitoring of quantity and quality parameters. As monitoring technologies 2 evolve, new possibilities of controlling and managing complex infrastructures are provided. This is the case for water networks. Sectorization of distribution networks into smaller subnetworks, such as District Metered Areas (DMAs), contributes to achieving, in real-time, an accurate estimation of the amount of water that is being consumed in each subnetwork. It is an efficient measure to control water loss, since flow and pressure meters bring a huge amount of data with information about the network behavior. Over the last decade, the concepts and methods developed for system-wide water balance calculations have been based upon water assets' physical data and the statistics of pipe bursts, service connections and underground conditions [1]. Performance measures and indicators are used to support the managerial approaches to minimize different components of water losses.Real-time monitoring of water networks is based on the use of sensor data from telemetry and mathematical models to detect and diagnose possible abnormal situations, such as leakage or water quality deterioration events. It links the real sensor data gathered from the network to the decision making procedure, by detecting possible faults as well as their probable location within the network. The main idea behind real-time monitoring, both for water balance and for water quality problems, is to use real-time sensor data and to compare them with those generated by a well-calibrated hydraulic model of the network in absence of faults. By analyzing the difference between these two sets of data, a detection of abnormal events can be performed.Several works have been published on leak detection and isolation methods for WDN.For example, a review of transient-based leak detection methods is offered in [2] as a summary of current and past work. In [3], a method has been proposed to identify leaks using blind spots based on previously leak detection researches that use the analysis of acoustic and vibrations signals [4], and models of buried pipelines to predict wave velocities [5]. ...
In this work, a decision support system (DSS) coupled with wastewater treatment plant (WWTP) simulator tool that uses a hierarchical set of key performance indicators (KPIs) to provide an assessment of the performance of WWTP systems is presented. An assessment of different Scenarios in a real WWTP case study, each consisting of a different set of sludge line technologies and derived combinations, was successfully conducted with the developed DSS–WWTP simulator, based on Scenario simulation and hierarchical KPI analysis. The test carried out on the selected WWTP showed that although thermal valorisation and thermal hydrolysis showed similar (the best) economic viability, the latter showed additional benefits, including synergies related to improving the thermal balance of the overall WWTP even when considering other technologies. On the other hand, biogas-upgrading technologies allowed reduction of emissions, but with higher costs and thermal demands. The usage of this tool may allow the development of proposals for technological priorities as a pathway to the transition to circular economy based on the management criteria of the correspondent sanitation system.
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