163,433 research outputs found

    Context-Aware Self-Organized Resource Allocation In Intelligent Water Informatics

    Full text link
    An increasing attention of intelligent water informatics has been registered in the recent years, specifically for monitoring water distribution systems. With a combination of smart sensor network technologies and water resource management systems, the intelligent water management system will be provided more easily to acquire the context information of water distribution systems, which aids to supply on a real-time monitoring/response/distribution framework through exchanging resource information in real time. In addition, endowing smart water grids with self-organizing capabilities is instrumental in helping operators cope with smart operations and maintenance. In this paper, we investigate the water resource allocation for heterogeneous smart water grids with context information. A water resource sharing algorithm is developed for efficient managing water resource in intelligent water informatics. Given the context information of water distribution grid, the reinforcement learning scheme, namely SWG-RL, is performed by virtue of two approaches: spectral clustering method and multi-agent reinforcement learning (RL). In the proposed SWG-RL scheme, the novel spectral clustering algorithm is proposed to cluster end-users into different communities with respect to the context information, and thereafter the community is modeled as an agent, which makes the online optimal decision for water resource allocation based on its interaction with the environment context dynamically. The proposed approach is tested and the numerical results show that the significant performance gain compared to conventional static schemes

    Predictive control applied to a water canal prototype

    Get PDF
    Predictive control is an intelligent tool to manage complex systems. This control strategy is getting more and more application in industrial fields. This paper shows the application of the predictive control methodology to a water distribution canal. Water canals are complex hydraulic systems because they are open and big scale systems, characterized by big delays and great inertia. Many models and control strategies have already been simulated using linear control theory. In the present study, a predictive control strategy is experimentally implemented in a modern automated canal prototype where sensors and actuators are controlled via a PLC network supervised by a SCADA system. The performance of this predictive controller is experimentally tested and very good results were obtained. The presented field studies show the potential of predictive control applied to water distribution canals and motivate its development for the management of water distribution networks in the near future

    Logique floue Appliquée à la gestion à long terme des ressources en eau

    Get PDF
    Dans le contexte de la rareté des ressources en eau, une approche globale de la gestion à long terme d'un système de stockage/transfert/distribution d'eau est proposée. L'objectif principal de la gestion d'un tel type de système est de gérer les réserves et les délestages de manière à minimiser les écarts entre offre et demande, ceci à partir d'une prédiction de la demande et des apports.Ainsi, on propose une approche à horizon glissant et surtout une procédure d'adaptation des pondérations du critère fondée sur la logique floue. Cette notion d'adaptation du critère parait tout à fait judicieuse quand on connaît la difficulté de définir les pondérations de tels problèmes d'optimisation et son influence sur la pertinence de la solution obtenue. On vérifie ici l'apport essentiel de la logique floue qui permet d'appréhender finement les enjeux en présence dans la gestion de long terme du système stockage/transfert/distribution d'eau. Le problème de gestion à long terme est résolu par une heuristique améliorée utilisant la programmation linéaire et la programmation dynamique pour réduire les effets de la discrétisation spatiale qui est si limitative dans ce contexte.L'approche de gestion proposée est effectivement appliquée à un cas d'étude qui permet de mettre en évidence sa relative simplicité de mise en œuvre.Since the origins of history, irrigation of agricultural lands has been reported to be an activity of great concern for many human societies. At the beginning, natural irrigation systems such as the Nile River flowing through the sands of Egypt have provided to neighbouring populations some amenities in their hard life. However irregular cycles of floods and droughts were a serious impediment to permanent settlements and to a continuous improvement of life conditions. Consequently human ingenuity has been continuously challenged by the development of new ways and means to master water resource system (WRS).During the last century, improved civil engineering techniques and the development of digital control systems and techniques have dramatically increased the power of human societies over their water resources. However many problems, which received some attention in the past, now require new approaches, given the steady increase in water demand and the introduction of environmental conservation considerations. Today, intelligent systems techniques appear to be able to give some insight in this direction by improving the efficiency of the different decision steps involved in the management and control of such systems. This paper focuses on the problem of the long-term management of a water resource system composed of a network of dams and river reaches. This system is viewed as a hybrid dynamic system, called here a storage/transfer/distribution system. The main long-term management objective of such a system is to manage reserves and releases so as to minimise the deficit between supply and demand by taking into account predictions of demand and contributions.Thus, in the present context of water resource scarcity, a complete approach for long-term management of a storage/transfer/distribution system is proposed. To take into account major uncertainties related to the operations of this kind of system, a sliding horizon approach (it consists of readjusting each week the release plan over the whole coming year, according to the present reserves, the most recent long-term demand estimation and the programmed release for the next week). In addition, an adaptation procedure of weighting parameters of the minimisation criterion based on fuzzy logic is implemented. The definition of an optimisation objective function is in this case a very intricate question since it involves competition, uncertainty and geographical dispersion. However, it is crucial to guarantee the quality of long-term management. This is why Fuzzy Logic is used as a particularly appropriate means to refine on-line the formulation of the objective function of the recurrent optimisation problem. Fuzzy Logic is also shown to be very useful in defining what is at stake in the long-term management. This criterion adaptation concept seems judicious, in view of the difficulty of defining the weighting parameters of such optimisation problems and their influence on the relevant solution obtained.The long-term management problem is solved with improved heuristics using linear programming and dynamic programming in order to reduce the effects of spatial discretisation, which is so restrictive in this context. The suggested approach is applied to a case study, which highlights its relative simplicity of implementation

    An ARTMAP-incorporated Multi-Agent System for Building Intelligent Heat Management

    Get PDF
    This paper presents an ARTMAP-incorporated multi-agent system (MAS) for building heat management, which aims to maintain the desired space temperature defined by the building occupants (thermal comfort management) and improve energy efficiency by intelligently controlling the energy flow and usage in the building (building energy control). Existing MAS typically uses rule-based approaches to describe the behaviours and the processes of its agents, and the rules are fixed. The incorporation of artificial neural network (ANN) techniques to the agents can provide for the required online learning and adaptation capabilities. A three-layer MAS is proposed for building heat management and ARTMAP is incorporated into the agents so as to facilitate online learning and adaptation capabilities. Simulation results demonstrate that ARTMAP incorporated MAS provides better (automated) energy control and thermal comfort management for a building environment in comparison to its existing rule-based MAS approach

    Intelligent comprehensive control and monitor of proton exchange membrane fuel cell for hybrid UPS system

    Full text link
    This paper, to improve the performance of a Proton Exchange Membrane fuel cell (PEMFC) stack, avoid the hydrogen and oxygen/air starvation of electrochemical reaction and the performance deterioration of the stack, prevent the dehydration and drying of the membrane, keep the water content in the membrane, heighten the utilization of the gases, and track the output power of a hybrid uninterruptible power supply (UPS) system with backup PEMFC and battery power sources, conducts research in the dynamic model, the on-line parameters monitoring of PEMFC, such as the resistance in the PEMFC stack using the current interrupt method and the performance improvement of the PEMFC employing an intelligent comprehensive control strategy of the operation parameters, such as operating temperature, pressures and mass flows of hydrogen and air, the output current and voltage for the PEMFC stack, the power supply switching between PEMFC and battery. The intelligent comprehensive control and monitor method is proposed and applied to the PEMFC generating system employed for the power source of UPS. The experimental results show that the proposal method can effectively monitor and control the pressures of the inlet hydrogen and the operating temperature of the stack, automatically switch the power supply between PEMFC and battery, efficaciously prevent the destroy of the stack when the load changes sharply, the hydrogen is purged and the output current is interrupted regularly, and reasonably improve the performance of the PEMFC through the water balance and thermal management, and real-time realize the tracking for the changes of the output power and the distribution of the mass flow rates of hydrogen and air. © 2009 IEEE

    Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

    Full text link
    New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption

    A Review on the Application of Natural Computing in Environmental Informatics

    Get PDF
    Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201
    corecore