ABB has introduced a water management platform that opens the door to new functions by bridging the gap between operational and information technologies. Basically an expert system equipped with reasoning capabilities, the platform’s ability to connect dots holds potentially enormous value in areas such as strategic planning, asset management and reporting, as it helps operators to spot anomalous conditions, identify the root causes of problems, compare patterns, and even simulate scenarios.
Marco Achilea, Gianluca Rolandelli Power & Water, ABB Energy Industries Genoa, Italy, firstname.lastname@example.org, email@example.com
Water resources and related infrastructures are experiencing an unprecedented array of challenges. These include increasing levels of water scarcity, growing coastal salinity, pollution, infrastructure degradation, tightening regulations, and the limited willingness of many governments and communities to recognize the crucial economic impact of these threats. As a result, operators of water systems are responding with a renewed focus on efficiency, which is being driven by adopting an increasingly data-driven approach to operations – a strategy designed to increase the transparency of systems throughout their networks, thus supporting a process of steadily improving decision making and improved handling of unplanned events.
In view of these developments, ABB has introduced its Water Management System (WMS) software solution, a highly extensible and configurable platform. The platform allows operators to completely integrate existing third-party components, be they systems or devices, regardless of their interfaces or application verticalizations. This bridges the gap between operational technologies and information technology layers and opens the door to new functions →01. This ability to connect dots holds potentially enormous value in areas such as strategic planning, asset management, and reporting, as it helps operators to spot anomalous conditions, identify the root causes of problems, compare patterns, and even simulate scenarios.
Deep domain knowledge
Designed to be an expert system for water utilities, ABB’s WMS employs knowledge about its application domain and uses an inferencing (reasoning) procedure to solve problems that would otherwise require mixed human competence or expertise combined with huge computational capability.
WMS’s power stems primarily from its deep domain knowledge, which is based on project experience and collaborations with customers. It also benefits from ABB’s partnership with DHI, a leading global advisory company specialized in water management and related ecosystems . Thanks to this collaboration, WMS is capable of modelling complex systems and providing insights into hydraulics.
The platform’s design →02 is based on several fully decoupled and modular layers that allow it to integrate data sources, regardless of whether they are external systems or IoT devices. Furthermore, thanks to an homogenization layer made up of custom connectors, it is possible to integrate and contextualize disparate data elements and store them in a cognitive model or cognitive data lake that is industry specific and understands the industry context.
As these processes take place, data converges toward middleware that offers transversal services, while being particularly cognizent of security considerations such as access control and data exchange, as well as performance considerations, such as caching mechanisms, data ingestion and storage, and message brokering. The end result is a “single-view cockpit” web application →03 that is complemented by a fully-responsive HMI (human machine interface) that balances design and usability.
ABB’s Water Management System offers a range of applications. Thanks to its high level of modularity and scalability, it can help water companies tackle the following challenges:
• Real-time operations monitoring based on a data collection layer and a data lake tailored to a water distribution network data model
• Leakage detection based on a water balance module capable of calculating the performance of each district or district metered area (a discrete part of a water distribution network)
• Report automation that can run and export pre-built reporting templates (eg, for regulation authorities) or ad-hoc reports
• Advanced simulation with a geospatial digital twin feature relying on a dynamic hydraulic model running on the back-end
• Water quality based on an ad hoc module that can monitor water age, contaminant events, and relevant water quality KPIs
Moreover, WMS fits into the broader ABB Ability™ offering, thus empowering real-time, data-driven decisions that maximize resource efficiency and contribute to a more sustainable world. The platform can collect data from any kind of source thanks to its IoT / connectivity layer, which can leverage the full capabilities of the ABB Ability Genix platform in terms of data collected from field / remote sites (including telemetry and data from low bandwidth connections eg via radio bridges).
The platform can also collect data from pre-existing SCADAs (or other third party systems) and /or directly from the field (including smart meters or IoT devices) through OPC UA/DA, MQTT, AMQP protocols. Finally, all data are harmonized and stored in the data lake for the apps and the WMS.
WMS MODULES: HELPING CUSTOMERS OVERCOME CHALLENGES
District performance allows real time analysis of water management performance based on inflows and consumption data as retrieved by the supervisory control and data acquisition (SCADA) system. For each area, WMS reports different KPIs, such as water leakages and related costs, including all standardized IWA parameters. Additional local parameters and indicators are available on demand. Based on real time data, the tool automatically detects new bursts and anomalies and generates alarms according to predefined rules and thresholds. In addition, the module facilitates the dissemination of data to authorities with a view to supporting daily operations and long-range planning of financial and technical resources in reducing leakages.
Network twin enables a real-time replica of a water network based on hydraulic modelling and data from SCADA. WMS automatically retrieves information from all sensors in a network in order to simulate the state of all controllable structures, such as valves, pumps, etc., together with the water levels in tanks, water demand, etc. A hydraulic model that replicates the network is automatically prepared by the system, allowing the representation of discharges, pressures, and water quality in each pipe. This makes it possible to better understand the behavior of the network and support operations and optimizations based on automatic warnings when anomalies are detected. The platform also makes it possible to dynamically compare real observations and simulated data in order to check model accuracy.
Network Scenario Manager includes a wide range of advanced analyses based on the availability of the hydraulic model. As previously mentioned, “Network Twin” offers real-time simulation of a network’s condition. Scenario Manager, on the other hand, allows the user to run advanced analyses both in terms of hindcast and forecast simulations. The hindcast module allows the simulation of past conditions, taking into account the state of all controllable structures as observed physical variables (water levels, water demands, etc.).
The forecast module makes it possible to simulate future conditions several days in advance based on predefined water demand profiles. What-if scenario simulations make it possible to compare alternative operations in the network (opening or closure of valves, changes in set points, etc.) as well as in terms of water demand. The WMS graphical interface helps the user to compare model results and identify best practices as optimization strategies.
This module includes real-time online analysis of water quality in the network in terms of water age and specific solutes, including routing from different sources. Quality data is collected and visualized for immediate monitoring of KPIs. Moreover, virtual sensors and digital twins can be used in order to run advanced simulations regarding water age estitimation, source tracing evaluation, and contaminat event what-if analysis.
This feature provides advanced analytics and integrated views of assets (pumps, motors, pipes, pressure relief valves, storage tanks, etc). This includes analytics on asset performance, health deviations, preventive maintenance, failures, corrective maintenance, asset event history and cost of maintenance, including generation of specific alerts in case of deviations.
As this module evolves, equipment failure predictions based on data-driven algorithms will be possible. These will analyze the behavior of a group of historical parameters to estimate time to failure (eg, predict performance degradation of a pump).
This module, which is based on embedded AI/ML techniques, is designed to improve performance (hence reduce overall cost) on a real-time basis. Optimum outputs in the form of setpoints, advisories, etc., are communicated to registered users to support insights, planning and actions. The module has the capability to model the development of processes, balances, and assets, as well as the ability to optimize the same based on analytical insights. It can also build soft sensors, thus minimizing physical deployment. Optimizations can be performed for energy efficiency (eg, network energy balance), asset performance (eg, variable best efficiency point), and processes (eg, flow balance).
 ABB. ABB andDHI Join Forces.Available at: https://new.abb.com/news/detail/84125/abb-and-dhi-groupjoin-forces-to-create-smarter-moresustainable-watermanagement-solutions[Accessed November19, 2021].
Title photo: Michelle Kiener