Smart water networks integrate sensor data, computation, control, and communication technologies to enhance system performance, reliability and consumer satisfaction. The cyber-physical systems are built from, and rely upon, the tight integration of physical elements of real-time sensors and data integration and cyber algorithmic, control computational and communication layers. A cyber-physical testbed has been developed at Texas A&M University at Qatar to simulate a real smart water network for research, education, and technology development purposes. The physical components include pipes, an automated pump-storage system, programmable logic controllers, controllable valves, a disinfectant injector, sensors, and data acquisition devices. Flow, pressure, temperature, and specific water quality parameters, such as pH and conductivity are continuously monitored by sensors, providing an operator with an up-to-date performance of the current state of the system. The pump-storage system is controlled by programmable logic controllers, and are designed to enable evaluation and enhancement of feedback and model-predictive control algorithms physically. The water tank is equipped with heating apparatus to conduct experimental studies for understanding the effect of water temperature on the fate and transport of chlorine and disinfection byproducts in the drinking water distribution of Qatar. The physical facility is integrated with a cyber-data acquisition and communications layer, and a cloud-based data storage, analytics, and visualization platform. Acquired data is stored and maintained in the format of a non-relational database on a cloud storage service. Additionally, a MongoDB server is set up to query and write data records. The analytics backend engine performs a variety of data transforms including, but not limited to, data cleansing and time series imputation and forecast. The visualization frontend provides a graphical interface to allow the operators interact with the backend engine by doing queries, plotting time series, running data analytics tasks, and generating reports. Together, this integrated physical and cyber layers unleash opportunities for education, research, development, evaluation, and commercialization of a variety of smart water networks technologies. It provides an environment that can predict leaks and pipe bursts based on real-time analytics of high-frequency pressure readings data on the cloud. This also enables developing smart pump-storage control technologies that help reducing non-revenue water loss, energy costs, and carbon emissions. The research team is also investigating harnessing the profound solar power resources available in Qatar for powering treatment plants and pumps by innovating control strategies that can handle the intermittency of such renewable power sources. Two asset management models are also developed and implemented on the testbed. (1) Performance assessment model of water distribution systems, which comprises four assessment modules for water pipelines, water accessories, water segments, and water networks. The model identifies critical factors affecting the performance of a water network and schedules pipe maintenance and replacement plans. (2) Risk assessment model for water pipelines failure, which evaluates the risks of performance and mechanical failures and applies a hierarchical fuzzy model to determine the risk using four risk factors as inputs (i.e., environmental, physical, operational, and post-failure). In addition to the research and technology purposes, this testbed has also provided a valuable learning resource for both operators and students. There are already several undergraduate students who are involved in design and construction of this facility. This has created an opportunity to train, educate, and empower undergraduate students, the future engineers and industry leaders of Qatar.


Article metrics loading...

Loading full text...

Full text loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error