IoT for Supervision and Control of Water Systems
Partners
Federal University of Minas Gerais, Centro de Pesquisas Hidráulicas e Recursos Hídricos
Liege University, Research group Hydraulics in Environmental and Civil Engineering
Institut national des sciences appliquées de Rouen, LITIS LAB, MIND Group
Ingenieurgesellschaft GmbH, Aachen
Abstract
Water transport and distribution systems must be carefully monitored and operated to avoid water losses, to save energy and to protect the assets of the water utilities against damage. In major water transport and distribution systems this task is performed by centralized SCADA (Supervisory Control and Data Acquisition) systems which receive information from remote sensors and remotely control components like valves and pumps. SCADA systems, however, are technically complex and expensive. For this reason, they are often not achievable for small water utilities which do have to operate their transport lines and distribution networks manually. Recent developments in ICT (Information and Communications Technology) open new paths for technologically advanced, however low-cost solutions for water system monitoring and control. In the first place it is the decentralized IoT (Internet of Things) approach which already gained significant importance in the industrial sector but is still in an embryonal stage considering water utilities. To explore the promising potential of IoT technologies in combination with other innovative ICT the IoT.H2O project sets up an interdisciplinary consortium.The project proposal follows a systematic approach starting with high time resolution measurements in water systems (already based on IoT technology), numerical description and characterization of the water systems, adaptation and development of hydraulic models suitable for near-real-time simulation, development of tools for implementation in IoT nodes for optimizing of component operation (e.g. pump operation / condition monitoring) and for supporting decision making (e.g. energy efficient reservoir management, alarm generation in case of incidents like pipe bursts, urban flashflood etc.), testing and system comparison by use of “water system digital twins” and physical water system models. The overall IoT system will be installed in systems in Belgium, Brazil and Germany for extended field testing and demonstration. Further application in other water utilities will be supported by documentation of the used methodology. The outcome of the project will be a new ICT approach for low-cost water system monitoring and operation. This system will contribute to water loss reduction, backing the efforts against impacts of water scarcity, simpler maintenance strategies and strengthening of water systems resilience against havocs.
Project structure:
WP1: Water network modelling: Modelling water networks, model evaluation and control systems comparison.
WP1.1: Computational modelling: (CPH) Developing computational hydraulic models of distribution networks (refer to WP6).
WP1.2: Model validating: (CPH) Validating computational model using reduced physical water distribution network model.
WP1.3: Control comparison: (CPH) Comparing SCADA and IoT control concepts at physical water network model.
WP2: Placing and virtual sensors: Optimized placing of IoT nodes and network components, development of virtual sensors.
WP2.1: IoT nodes placing: (HECE) Optimized placing of IoT nodes (flow,pressure, others) using hydraulic methodology.
WP2.2: Virtual sensors: (HECE) Development of hydraulic model based virtual sensors for water quality (e.g. residual chlorine, water aging)
WP2.3: Energy recovery: (HECE) Hydraulic model based placing and sizing of energy recovery systems (including robust estimation of energy production potential and economic value).
WP3: Pump operation: Optimization of pump operation and condition monitoring
WP3.1: Energy efficient pump operation: (SAM) Hydraulic model supported energy efficiency optimized Pump operation.
WP3.2: Pressure management: (SAM) Model supported pump control for intelligent pressure management.
WP3.3: Condition monitoring: (SAM) Adapting / developing IoT condition monitoring sensors for pumps, lab and field testing.
WP4: Multiagent technology: Development of Multiagent technology for decentralized AI – Artificial Intelligence for water networks operation.
WP4.1: Demand driven optimization: (LITIS) Development of optimization strategies for demand driven water network optimization.
WP4.2: Incident recognition: (LITIS) Development / implementation of incident recognition algorithms (pipe bursts, urban flash flood incidents, situation adapted generation of alarms).
WP4.3: Incident Recovery: (LITIS) Development/implementation of incident recovery algorithms to increase resiliency
WP5: IoT network and digital twin: Developing, adapting and testing of water systems adequate IoT networks and sensing systems, water system digital twin.
WP5.1: IoT network: (KI) Selection, developing protypes of task-specific IoT network(s) including sensors for pressure and flow, functional laboratory and field testing. (Field layer, network layer, application layer.)
WP5.2: IoT system: (KI) Setting up of an integrated pilot IoT system (pressure / flow nodes, gateway, application), laboratory and field testing.
WP5.3: Digital twin and IoT: (KI) Developing simplified hybrid models (digital twin and real sensors) of water networks for testing IoT concept and optimization of controls.
WP6: Field deployment: (Field) survey, field deployment of components for testing, setting up of an integrated IoT system.
WP6.1: Network selection: (All): Selection of networks for field tests and modelling (water utilities in Belo Horizonte, Liege, Kaiserslautern).
WP6.2: Network survey: (All): Studying selected water networks, collection of network data and characteristics.
WP6.3: Components testing: (All) Testing of individual components (IoT devices, gateways, networks).
WP6.4: System test: (All) Testing complete field installations and integrated IoT system. Evaluation.
WP7: Project management: Project management
WP7.1: Project coordination: (SAM) Project coordination
WP7.2: Project communication: (SAM) Implementation / operation of cloud service for data exchange, communication.
WP7.3: Project meetings: (All) Kick-off meeting, project meetings
WP7.4: Dissemination
Outcomes and expected impact:
Outcomes: