Overview of Energy Management and Leakage Control Systems for Smart Water Grids and Digital Water

Current and future smart cities are moving towards the zero-net energy use concept. To this end, the built environment should also be designed for efficient energy use and play a significant role in the production of such energy. At present, this is achieved by focusing on energy demand in buildings and to the renewable trade-off related to smart power grids. However, urban water distribution systems constantly carry an excess of hydraulic energy that can potentially be recovered to produce electricity. This paper presents a comprehensive review of current strategies for energy production by reviewing the state-of-the-art of smart water systems. New technologies (such as cyber-physical systems, digital twins, blockchain) and new methodologies (network dynamics, geometric deep learning) associated with digital water are also discussed. The paper then focuses on modelling the installation of both micro-turbines and pumps as turbines, instead of/together with pressure reduction valves, to further demonstrate the energy-recovery methods which will enable water network partitioning into district metered areas. The associated benefits on leakage control, as a source of energy, and for contributing to overall network resilience are also highlighted. The paper concludes by presenting future research directions. Notably, digital water is proposed as the main research and operational direction for current and future Water Distribution Systems (WDS) and as a holistic, data-centred framework for the operation and management of water networks.</jats:p

Gestión inteligente de sistemas de distribución de agua

The United Nations predicts that the world's population in 2050 will reach 9.7 billion people. This exponential growth will mean an increase in the global demand for water available for human consumption. In addition, the advance of climate change is causing the occurrence of more frequent droughts, especially in arid and semi-arid areas. Indirectly, this means an increase in the costs associated with water transport and purification, as water must be drawn from sources that are increasingly distant from the points of consumption and the quality is getting worse. The traditional management of urban water supply is changing towards a more sustainable model aimed at an efficient use of resources (water, energy, labour) that not only reduces management costs but is also more environmentally friendly. This transformation is taking place due to the development of other transversal disciplines (cloud computing, communication systems, Big Data, electronics, etc.) applied to many fields of science, which applied to water management, can bring considerable benefits. Furthermore, to achieve intelligent management of a water supply network, it is necessary to rely on current tools that provide objective knowledge of the system. For example, geographic information systems (GIS) together with hydraulic models serve as a georeferenced database where the behaviour of any hydraulic network in different scenarios can be simulated. The Internet of Things (IoT) allows the connection of a network of sensors to know the main hydraulic variables at any time, providing key information for hydraulic models to faithfully reproduce the behaviour of modelled systems in real time. Digitalisation itself favours the use of information and communication technologies (ICT) to convert traditional management into smart management. For these reasons, new studies are needed to assess the potential and applicability of these new tools. This thesis is organised in 6 chapters focused on the development and application of a decision support system that allow the manager of a water supply network to make decisions based on data recorded on real-time. All the tools developed throughout this thesis have been tested in a real water supply network located in the south of Spain, managed by the Provincial Water Company of Cordoba (EMPROACSA). Chapter 1 shows the trajectory of urban supply management: explaining the starting point and where it is expected to achieve. Then, Chapter 2 describes the main objective and the specific objectives of this thesis, as well as the structure of this document. Chapter 3 presents a methodology that serves as a basis for starting the digitisation process in water supply networks. The system developed is based on three pillars: the geographic information system, the hydraulic model, and the application for mobile devices. The geographic information system provides a georeferenced database of the infrastructures that compose the hydraulic network; the hydraulic model simulates the response of the network to different operation scenarios; and finally, the mobile application facilitates the feedback of the system to keep it always up to date with changes in the systems. One of the distinguishing features of this work is the use of free software (Qgis, Epanet and Google My Maps) in all stages, which fosters digitisation in supply companies with a low budget. Chapter 4 develops an early warning system based on water pressure monitoring. The communication node developed ad-hoc for this work, sends water pressure data to the cloud, where users can visualise them with a device with an internet connection. Among its advantages are its low cost, it allows the use of different communication systems and has a high autonomy powered by batteries, which makes it well adapted to supply systems. The proposed monitoring system detects failures in the network due to pressure drops, alerting managers of the affected zone. Chapter 5 explains the decision support tool developed to deal with failures in water transmission networks. The web platform that supports this tool is divided into 3 independent modules: fault detection, alerts, and fault repair. The first module is responsible for detecting, geolocating and classifying faults in the hydraulic network using the information recorded in real time by the pressure monitoring system described in the previous chapter. The second module is responsible for sending alerts selectively to the workers in the area of the failure. Finally, the third module estimates, applying the hydraulic model, the maximum time that the manager has to fix failures, avoiding supply cuts using the water stored in regulation tanks when the failure occurs. The fault detection and classification module has demonstrated a 95% accuracy when applied to a real case. Chapter 6 contains the general conclusions of the thesis, as well as possible lines of future work. In summarise, water management is experiencing a paradigm shift. This transformation requires sufficiently mature technologies to ensure good results. Therefore, studies are needed that not only advance towards smart management, but also evaluate the tools available now and their integration into the current management model. This thesis presents a decision support system applied to supply networks, which help managers to make decisions based on objective information, not on intuition or experience. The use of open-source software and hardware in all the developments of this thesis must be emphasised. This specific feature allows the adoption of the methodologies proposed by water companies, regardless of size or financial resources, enabling the whole system or only part of it to be adapted to the operation of the company.Las Naciones Unidas prevén que la población mundial en 2050 alcanzará los 9.700 millones de personas. Este crecimiento exponencial supondrá un aumento de la demanda global de agua disponible para el consumo humano. Además, el avance del cambio climático está provocando la aparición de sequías más frecuentes, especialmente en las zonas áridas y semiáridas. Indirectamente, esto supone un aumento de los costes asociados al transporte y la depuración del agua, ya que hay que extraerla de fuentes cada vez más alejadas de los puntos de consumo y la calidad es cada vez peor. La gestión tradicional del abastecimiento de agua en las ciudades está cambiando hacia un modelo más sostenible orientado a un uso eficiente de los recursos (agua, energía, mano de obra) que además de reducir los costes de gestión, es más respetuoso con el medio ambiente. Esta transformación se está produciendo gracias al desarrollo de otras disciplinas transversales (computación en la nube, sistemas de comunicación, Big Data, electrónica, etc.) aplicadas a diversos campos de la ciencia, que aplicadas a la gestión del agua, pueden aportar considerables beneficios. Además, para conseguir una gestión inteligente de una red de abastecimiento de agua, es necesario apoyarse en herramientas actuales que proporcionen un conocimiento objetivo del sistema. Por ejemplo, los sistemas de información geográfica (SIG) junto con los modelos hidráulicos sirven como base de datos georreferenciada donde se puede simular el comportamiento de cualquier red hidráulica en diferentes escenarios. El Internet de las Cosas (IoT) permite la conexión de una red de sensores para conocer las principales variables hidráulicas en cada momento, aportando información clave para que los modelos hidráulicos reproduzcan fielmente el comportamiento de los sistemas modelizados en tiempo real. La propia digitalización favorece el uso de las tecnologías de la información y la comunicación (TIC) para convertir la gestión tradicional en una gestión inteligente. Por estas razones, son necesarios nuevos estudios para evaluar el potencial y la aplicabilidad de estas nuevas herramientas. Esta tesis se organiza en 6 capítulos centrados en el desarrollo y aplicación de un sistema de apoyo a la decisión que permita al gestor de una red de abastecimiento de agua tomar decisiones basadas en datos registrados en tiempo real. Todas las herramientas desarrolladas a lo largo de esta tesis han sido probadas en una red real de abastecimiento de agua situada en el sur de España, gestionada por la Empresa Provincial de Aguas de Córdoba (EMPROACSA). El capítulo 1 muestra la trayectoria de la gestión del abastecimiento urbano: explicando el punto de partida y hacia dónde se espera llegar. A continuación, el capítulo 2 describe el objetivo principal y los objetivos específicos de esta tesis, así como la estructura de este documento. El capítulo 3 presenta una metodología que sirve de base para iniciar el proceso de digitalización de las redes de abastecimiento de agua. El sistema desarrollado se basa en tres pilares: el sistema de información geográfica, el modelo hidráulico y la aplicación para dispositivos móviles. El sistema de información geográfica proporciona una base de datos georreferenciada de las infraestructuras que componen la red hidráulica; el modelo hidráulico simula la respuesta de la red ante diferentes escenarios de operación; y, por último, la aplicación móvil facilita la retroalimentación del sistema para mantenerlo siempre actualizado con los cambios en los sistemas. Uno de los rasgos distintivos de este trabajo es el uso de software libre (Qgis, Epanet y Google My Maps) en todas las etapas, lo que favorece la digitalización en empresas de abastecimiento con bajo presupuesto. El capítulo 4 desarrolla un sistema de alerta temprana basado en la monitorización de la presión del agua. El nodo de comunicación desarrollado ad-hoc para este trabajo, envía los datos de la presión del agua a la nube, donde los usuarios pueden visualizarlos con un dispositivo con conexión a internet. Entre sus ventajas están su bajo coste, permite el uso de diferentes sistemas de comunicación y tiene una gran autonomía alimentada por baterías, lo que hace que se adapte bien a los sistemas de abastecimiento. El sistema de monitorización propuesto detecta fallos en la red por caídas de presión, alertando a los gestores de la zona afectada. El capítulo 5 explica la herramienta de apoyo a la toma de decisiones desarrollada para hacer frente a las averías en las redes de abastecimiento en alta. La plataforma web, que soporta esta herramienta, se divide en 3 módulos independientes: detección de averías, alertas y reparación de averías. El primer módulo se encarga de detectar, geolocalizar y clasificar las averías en la red hidráulica a partir de la información registrada en tiempo real por el sistema de monitorización de presiones descrito en el capítulo anterior. El segundo módulo se encarga de enviar alertas de forma selectiva a los trabajadores de la zona de la avería. Por último, el tercer módulo estima, aplicando el modelo hidráulico, el tiempo máximo del que dispone el gestor para solucionar las averías, evitando los cortes de suministro con el agua almacenada en los depósitos de regulación cuando se produce la avería. El módulo de detección y clasificación de averías ha demostrado una precisión del 95% cuando se aplica a un caso real. El capítulo 6 contiene las conclusiones generales de la tesis, así como posibles líneas de trabajo futuras. En resumen, la gestión del agua está experimentando un cambio de paradigma. Esta transformación requiere tecnologías suficientemente maduras para garantizar buenos resultados. Por ello, son necesarios estudios que no sólo avancen hacia una gestión inteligente, sino que evalúen las herramientas disponibles en la actualidad y su integración en el modelo de gestión actual. Esta tesis presenta un sistema de apoyo a la decisión aplicado a las redes de suministro de agua, que ayuda a los gestores a tomar decisiones basadas en información objetiva y no en la intuición o la experiencia. Cabe destacar el uso de software y hardware de código abierto en todos los desarrollos de esta tesis. Esta particularidad permite la adopción de las metodologías propuestas por las empresas de agua, independientemente de su tamaño o recursos financieros, permitiendo adaptar todo el sistema o sólo una parte de él al funcionamiento de la empresa

Wearables for independent living in older adults: Gait and falls

Solutions are needed to satisfy care demands of older adults to live independently. Wearable technology (wearables) is one approach that offers a viable means for ubiquitous, sustainable and scalable monitoring of the health of older adults in habitual free-living environments. Gait has been presented as a relevant (bio)marker in ageing and pathological studies, with objective assessment achievable by inertial-based wearables. Commercial wearables have struggled to provide accurate analytics and have been limited by non-clinically oriented gait outcomes. Moreover, some research-grade wearables also fail to provide transparent functionality due to limitations in proprietary software. Innovation within this field is often sporadic, with large heterogeneity of wearable types and algorithms for gait outcomes leading to a lack of pragmatic use. This review provides a summary of the recent literature on gait assessment through the use of wearables, focusing on the need for an algorithm fusion approach to measurement, culminating in the ability to better detect and classify falls. A brief presentation of wearables in one pathological group is presented, identifying appropriate work for researchers in other cohorts to utilise. Suggestions for how this domain needs to progress are also summarised

Seismological data acquisition and signal processing using wavelets

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This work deals with two main fields: a) The design, built, installation, test, evaluation, deployment and maintenance of Seismological Network of Crete (SNC) of the Laboratory of Geophysics and Seismology (LGS) at Technological Educational Institute (TEI) at Chania. b) The use of Wavelet Transform (WT) in several applications during the operation of the aforementioned network. SNC began its operation in 2003. It is designed and built in order to provide denser network coverage, real time data transmission to CRC, real time telemetry, use of wired ADSL lines and dedicated private satellite links, real time data processing and estimation of source parameters as well as rapid dissemination of results. All the above are implemented using commercial hardware and software which is modified and where is necessary, author designs and deploy additional software modules. Up to now (July 2008) SNC has recorded 5500 identified events (around 970 more than those reported by national bulletin the same period) and its seismic catalogue is complete for magnitudes over 3.2, instead national catalogue which was complete for magnitudes over 3.7 before the operation of SNC. During its operation, several applications at SNC used WT as a signal processing tool. These applications benefited from the adaptation of WT to non-stationary signals such as the seismic signals. These applications are: HVSR method. WT used to reveal undetectable non-stationarities in order to eliminate errors in site’s fundamental frequency estimation. Denoising. Several wavelet denoising schemes compared with the widely used in seismology band-pass filtering in order to prove the superiority of wavelet denoising and to choose the most appropriate scheme for different signal to noise ratios of seismograms. EEWS. WT used for producing magnitude prediction equations and epicentral estimations from the first 5 secs of P wave arrival. As an alternative analysis tool for detection of significant indicators in temporal patterns of seismicity. Multiresolution wavelet analysis of seismicity used to estimate (in a several years time period) the time where the maximum emitted earthquake energy was observed

Roadmap on measurement technologies for next generation structural health monitoring systems

Structural health monitoring (SHM) is the automation of the condition assessment process of an engineered system. When applied to geometrically large components or structures, such as those found in civil and aerospace infrastructure and systems, a critical challenge is in designing the sensing solution that could yield actionable information. This is a difficult task to conduct cost-effectively, because of the large surfaces under consideration and the localized nature of typical defects and damages. There have been significant research efforts in empowering conventional measurement technologies for applications to SHM in order to improve performance of the condition assessment process. Yet, the field implementation of these SHM solutions is still in its infancy, attributable to various economic and technical challenges. The objective of this Roadmap publication is to discuss modern measurement technologies that were developed for SHM purposes, along with their associated challenges and opportunities, and to provide a path to research and development efforts that could yield impactful field applications. The Roadmap is organized into four sections: distributed embedded sensing systems, distributed surface sensing systems, multifunctional materials, and remote sensing. Recognizing that many measurement technologies may overlap between sections, we define distributed sensing solutions as those that involve or imply the utilization of numbers of sensors geometrically organized within (embedded) or over (surface) the monitored component or system. Multi-functional materials are sensing solutions that combine multiple capabilities, for example those also serving structural functions. Remote sensing are solutions that are contactless, for example cell phones, drones, and satellites. It also includes the notion of remotely controlled robots

High-Performance Modelling and Simulation for Big Data Applications

This open access book was prepared as a Final Publication of the COST Action IC1406 “High-Performance Modelling and Simulation for Big Data Applications (cHiPSet)“ project. Long considered important pillars of the scientific method, Modelling and Simulation have evolved from traditional discrete numerical methods to complex data-intensive continuous analytical optimisations. Resolution, scale, and accuracy have become essential to predict and analyse natural and complex systems in science and engineering. When their level of abstraction raises to have a better discernment of the domain at hand, their representation gets increasingly demanding for computational and data resources. On the other hand, High Performance Computing typically entails the effective use of parallel and distributed processing units coupled with efficient storage, communication and visualisation systems to underpin complex data-intensive applications in distinct scientific and technical domains. It is then arguably required to have a seamless interaction of High Performance Computing with Modelling and Simulation in order to store, compute, analyse, and visualise large data sets in science and engineering. Funded by the European Commission, cHiPSet has provided a dynamic trans-European forum for their members and distinguished guests to openly discuss novel perspectives and topics of interests for these two communities. This cHiPSet compendium presents a set of selected case studies related to healthcare, biological data, computational advertising, multimedia, finance, bioinformatics, and telecommunications