813 resultados para HT furnace energy management
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Paper presented at the 5th European Conference Economics and Management of Energy in Industry, Vilamoura, Algarve. Apr. 14-17, 2009, 11p. URL: http:// www.cenertec.pt/ecemei/
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa Para a obtenção do Grau de Mestre em Energia e Bioenergia
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The recent developments in neurobiology have rendered new prominence and potential to study about the structure and function of brain and related disorders. Human behaviour is the net result of neural control of the communication between brain cells. Neurotransmitters are chemicals that are used to relay, amplify and modulate electrical signals between neurons and/or another cell. It mediates rapid intercellular communication through the nervous system by interacting with cell surface receptors. These receptors often trigger second messenger signaling pathways that regulate the activity of ion channels. The functional balance of different neurotransmitters such as Acetylcholine (Ach), Dopamine (DA), Serotonin (5-HT), Norepinephrine (NE), Epinephrine (EPI), Glutamate and Gamma amino butyric acid (GABA) regulates the growth, division and other vital functions of a normal cell / organism (Sudha, 1998). Any change in neurotransmitters' functional balance will result in the failure of cell function and may lead to the occurrence of diseases. Abnormalities in the production or functioning of neurotransmitters have been implicated in a number of neurological disorders like Schizophrenia, Alzheimer's, Epilepsy, Depression and Parkinson's disease. Changes in central and peripheral neuronal signaling system is also noted in diabetes, cancer, cell proliferation, alcoholism and aging. Elucidation of neurotransmitters receptor interaction pathways and gene expression regulation by second messengers and transcriptional factors in health and disease conditions can lead to new small molecules for development of therapeutic agents to improve neurological disease conditions. Increased awareness of the global effects of neurological disorders should help health care planners and the neurological community set appropriate priorities in research, prevention, and management of these diseases.
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In the present scenario of energy demand overtaking energy supply top priority is given for energy conservation programs and policies. Most of the process plants are operated on continuous basis and consumes large quantities of energy. Efficient management of process system can lead to energy savings, improved process efficiency, lesser operating and maintenance cost, and greater environmental safety. Reliability and maintainability of the system are usually considered at the design stage and is dependent on the system configuration. However, with the growing need for energy conservation, most of the existing process systems are either modified or are in a state of modification with a view for improving energy efficiency. Often these modifications result in a change in system configuration there by affecting the system reliability. It is important that system modifications for improving energy efficiency should not be at the cost of reliability. Any new proposal for improving the energy efficiency of the process or equipments should prove itself to be economically feasible for gaining acceptance for implementation. In order to arrive at the economic feasibility of the new proposal, the general trend is to compare the benefits that can be derived over the lifetime as well as the operating and maintenance costs with the investment to be made. Quite often it happens that the reliability aspects (or loss due to unavailability) are not taken into consideration. Plant availability is a critical factor for the economic performance evaluation of any process plant.The focus of the present work is to study the effect of system modification for improving energy efficiency on system reliability. A generalized model for the valuation of process system incorporating reliability is developed, which is used as a tool for the analysis. It can provide an awareness of the potential performance improvements of the process system and can be used to arrive at the change in process system value resulting from system modification. The model also arrives at the pay back of the modified system by taking reliability aspects also into consideration. It is also used to study the effect of various operating parameters on system value. The concept of breakeven availability is introduced and an algorithm for allocation of component reliabilities of the modified process system based on the breakeven system availability is also developed. The model was applied to various industrial situations.
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In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay
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Data caching is an attractive solution for reducing bandwidth demands and network latency in mobile ad hoc networks. Deploying caches in mobile nodes can reduce the overall traf c considerably. Cache hits eliminate the need to contact the data source frequently, which avoids additional network overhead. In this paper we propose a data discovery and cache management policy for cooperative caching, which reduces the power usage, caching overhead and delay by reducing the number of control messages flooded into the network .A cache discovery process based on position cordinates of neighboring nodes is developed for this .The stimulstion results gives a promising result based on the metrics of the studies.
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A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.
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Vor dem Hintergund der Integration des wissensbasierten Managementsystems Precision Farming in den Ökologischen Landbau wurde die Umsetzung bestehender sowie neu zu entwickelnder Strategien evaluiert und diskutiert. Mit Blick auf eine im Precision Farming maßgebende kosteneffiziente Ertragserfassung der im Ökologischen Landbau flächenrelevanten Leguminosen-Grasgemenge wurden in zwei weiteren Beiträgen die Schätzgüten von Ultraschall- und Spektralsensorik in singulärer und kombinierter Anwendung analysiert. Das Ziel des Precision Farming, ein angepasstes Management bezogen auf die flächeninterne Variabilität der Standorte umzusetzen, und damit einer Reduzierung von Betriebsmitteln, Energie, Arbeit und Umwelteffekten bei gleichzeitiger Effektivitätssteigerung und einer ökonomischen Optimierung zu erreichen, deckt sich mit wesentlichen Bestrebungen im Ökogischen Landbau. Es sind vorrangig Maßnahmen zur Erfassung der Variabilität von Standortfaktoren wie Geländerelief, Bodenbeprobung und scheinbare elektrische Leitfähigkeit sowie der Ertragserfassung über Mähdrescher, die direkt im Ökologischen Landbau Anwendung finden können. Dagegen sind dynamisch angepasste Applikationen zur Düngung, im Pflanzenschutz und zur Beseitigung von Unkräutern aufgrund komplexer Interaktionen und eines eher passiven Charakters dieser Maßnahmen im Ökologischen Landbau nur bei Veränderung der Applikationsmodelle und unter Einbindung weiterer dynamischer Daten umsetzbar. Beispiele hiefür sind einzubeziehende Mineralisierungsprozesse im Boden und organischem Dünger bei der Düngemengenberechnung, schwer ortsspezifisch zuzuordnende präventive Maßnamen im Pflanzenschutz sowie Einflüsse auf bodenmikrobiologische Prozesse bei Hack- oder Striegelgängen. Die indirekten Regulationsmechanismen des Ökologischen Landbaus begrenzen daher die bisher eher auf eine direkte Wirkung ausgelegten dynamisch angepassten Applikationen des konventionellen Precision Farming. Ergänzend sind innovative neue Strategien denkbar, von denen die qualitätsbezogene Ernte, der Einsatz hochsensibler Sensoren zur Früherkennung von Pflanzenkrankheiten oder die gezielte teilflächen- und naturschutzorientierte Bewirtschaftung exemplarisch in der Arbeit vorgestellt werden. Für die häufig große Flächenanteile umfassenden Leguminosen-Grasgemenge wurden für eine kostengünstige und flexibel einsetzbare Ertragserfassung die Ultraschalldistanzmessung zur Charakterisierung der Bestandeshöhe sowie verschiedene spektrale Vegetationsindices als Schätzindikatoren analysiert. Die Vegetationsindices wurden aus hyperspektralen Daten nach publizierten Gleichungen errechnet sowie als „Normalized Difference Spectral Index“ (NDSI) stufenweise aus allen möglichen Wellenlängenkombinationen ermittelt. Die Analyse erfolgte für Ultraschall und Vegetationsindices in alleiniger und in kombinierter Anwendung, um mögliche kompensatorische Effekte zu nutzen. In alleiniger Anwendung erreichte die Ultraschallbestandeshöhe durchweg bessere Schätzgüten, als alle einzelnen Vegetationsindices. Bei den letztgenannten erreichten insbesondere auf Wasserabsorptionsbanden basierende Vegetationsindices eine höhere Schätzgenauigkeit als traditionelle Rot/Infrarot-Indices. Die Kombination beider Sensorda-ten ließ eine weitere Steigerung der Schätzgüte erkennen, insbesondere bei bestandesspezifischer Kalibration. Hierbei kompensieren die Vegetationsindices Fehlschätzungen der Höhenmessung bei diskontinuierlichen Bestandesdichtenänderungen entlang des Höhengradienten, wie sie beim Ährenschieben oder durch einzelne hochwachsende Arten verursacht werden. Die Kombination der Ultraschallbestandeshöhe mit Vegetationsindices weist das Potential zur Entwicklung kostengünstiger Ertragssensoren für Leguminosen-Grasgemenge auf. Weitere Untersuchungen mit hyperspektralen Vegetationsindices anderer Berechnungstrukturen sowie die Einbindung von mehr als zwei Wellenlängen sind hinsichtlich der Entwicklung höherer Schätzgüten notwendig. Ebenso gilt es, Kalibrierungen und Validationen der Sensorkombination im artenreichen Grasland durchzuführen. Die Ertragserfassung in den Leguminosen-Grasgemengen stellt einen wichtigen Beitrag zur Erstellung einer Ertragshistorie in den vielfältigen Fruchtfolgen des Ökologischen Landbaus dar und ermöglicht eine verbesserte Einschätzung von Produktionspotenzialen und Defizitarealen für ein standortangepasstes Management.
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The demand for biomass for bioenergy has increased rapidly in industrialized countries in the recent years. Biogenic energy carriers are known to reduce CO2 emissions. However, the resource-inefficient production of biomass often caused negative impacts on the environment, e.g. biodiversity losses, nitrate leaching, and erosion. The detrimental effects evolved mainly from annual crops. Therefore, the aim of modern bioenergy cropping systems is to combine yield stability and environmental benefits by the establishment of mixed-cropping systems. A particular emphasis is on perennial crops which are perceived as environmentally superior to annual crops. Agroforestry systems represent such mixed perennial cropping systems and consist of a mix of trees and arable crops or grassland within the same area of land. Agroforestry practices vary across the globe and alley cropping is a type of agroforestry system which is well adapted to the temperate zone, with a high degree of mechanization. Trees are planted in rows and crops are planted in the alleyways, which facilitates their management by machinery. This study was conducted to examine a young alley cropping system of willows and two grassland mixtures for bioenergy provision under temperate climate conditions. The first part of the thesis identified possible competition effects between willows and the two grassland mixtures. Since light seemed to be the factor most affecting the yield performance of the understory in temperate agroforestry systems, a biennial in situ artificial shade experiment was established over a separate clover-grass stand to quantify the effects of shade. Data to possible below- and aboveground interactions among willows and the two grassland mixtures and their effects on productivity, sward composition, and quality were monitored along a tree-grassland interface within the alleys. In the second part, productivity of the alley cropping system was examined on a triennial time frame and compared to separate grassland and willow stands as controls. Three different conversion technologies (combustion of hay, integrated generation of solid fuel and biogas from biomass, whole crop digestion) were applied to grassland biomass as feedstock and analyzed for its energetic potential. The energetic potential of willow wood chips was calculated by applying combustion as conversion technique. Net energy balances of separate grassland stands, agroforestry and pure willow stands evaluated their energy efficiency. Results of the biennial artificial shade experiment showed that severe shade (80 % light reduction) halved grassland productivity on average compared to a non-shaded control. White clover as heliophilous plant responded sensitively to limited radiation and its dry matter contribution in the sward decreased with increasing shade, whereas non-leguminous forbs (mainly segetal species) benefited. Changes in nutritive quality could not be confirmed by this experiment. Through the study on interactions within the alleys of the young agroforestry system it was possible to outline changes of incident light, soil temperature and sward composition of clover-grass along the tree-grassland interface. Nearly no effects of trees on precipitation, soil moisture and understory productivity occurred along the interface during the biennial experiment. Considering the results of the productivity and the net energy yield alley cropping system had lower than pure grassland stands, irrespective of the grassland seed mixture or fertilization, but was higher than that for pure willow stands. The comparison of three different energetic conversion techniques for the grassland biomass showed highest net energy yields for hay combustion, whereas the integrated generation of solid fuel and biogas from biomass (IFBB) and whole crop digestion performed similarly. However, due to the low fuel quality of hay, its direct combustion cannot be recommended as a viable conversion technique, whereas IFBB fuels were of a similar quality to wood chip from willow.
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Una de las actuaciones posibles para la gestión de los residuos sólidos urbanos es la valorización energética, es decir la incineración con recuperación de energía. Sin embargo es muy importante controlar adecuadamente el proceso de incineración para evitar en lo posible la liberación de sustancias contaminantes a la atmósfera que puedan ocasionar problemas de contaminación industrial.Conseguir que tanto el proceso de incineración como el tratamiento de los gases se realice en condiciones óptimas presupone tener un buen conocimiento de las dependencias entre las variables de proceso. Se precisan métodos adecuados de medida de las variables más importantes y tratar los valores medidos con modelos adecuados para transformarlos en magnitudes de mando. Un modelo clásico para el control parece poco prometedor en este caso debido a la complejidad de los procesos, la falta de descripción cuantitativa y la necesidad de hacer los cálculos en tiempo real. Esto sólo se puede conseguir con la ayuda de las modernas técnicas de proceso de datos y métodos informáticos, tales como el empleo de técnicas de simulación, modelos matemáticos, sistemas basados en el conocimiento e interfases inteligentes. En [Ono, 1989] se describe un sistema de control basado en la lógica difusa aplicado al campo de la incineración de residuos urbanos. En el centro de investigación FZK de Karslruhe se están desarrollando aplicaciones que combinan la lógica difusa con las redes neuronales [Jaeschke, Keller, 1994] para el control de la planta piloto de incineración de residuos TAMARA. En esta tesis se plantea la aplicación de un método de adquisición de conocimiento para el control de sistemas complejos inspirado en el comportamiento humano. Cuando nos encontramos ante una situación desconocida al principio no sabemos como actuar, salvo por la extrapolación de experiencias anteriores que puedan ser útiles. Aplicando procedimientos de prueba y error, refuerzo de hipótesis, etc., vamos adquiriendo y refinando el conocimiento, y elaborando un modelo mental. Podemos diseñar un método análogo, que pueda ser implementado en un sistema informático, mediante el empleo de técnicas de Inteligencia Artificial.Así, en un proceso complejo muchas veces disponemos de un conjunto de datos del proceso que a priori no nos dan información suficientemente estructurada para que nos sea útil. Para la adquisición de conocimiento pasamos por una serie de etapas: - Hacemos una primera selección de cuales son las variables que nos interesa conocer. - Estado del sistema. En primer lugar podemos empezar por aplicar técnicas de clasificación (aprendizaje no supervisado) para agrupar los datos y obtener una representación del estado de la planta. Es posible establecer una clasificación, pero normalmente casi todos los datos están en una sola clase, que corresponde a la operación normal. Hecho esto y para refinar el conocimiento utilizamos métodos estadísticos clásicos para buscar correlaciones entre variables (análisis de componentes principales) y así poder simplificar y reducir la lista de variables. - Análisis de las señales. Para analizar y clasificar las señales (por ejemplo la temperatura del horno) es posible utilizar métodos capaces de describir mejor el comportamiento no lineal del sistema, como las redes neuronales. Otro paso más consiste en establecer relaciones causales entre las variables. Para ello nos sirven de ayuda los modelos analíticos - Como resultado final del proceso se pasa al diseño del sistema basado en el conocimiento. El objetivo principal es aplicar el método al caso concreto del control de una planta de tratamiento de residuos sólidos urbanos por valorización energética. En primer lugar, en el capítulo 2 Los residuos sólidos urbanos, se trata el problema global de la gestión de los residuos, dando una visión general de las diferentes alternativas existentes, y de la situación nacional e internacional en la actualidad. Se analiza con mayor detalle la problemática de la incineración de los residuos, poniendo especial interés en aquellas características de los residuos que tienen mayor importancia de cara al proceso de combustión.En el capítulo 3, Descripción del proceso, se hace una descripción general del proceso de incineración y de los distintos elementos de una planta incineradora: desde la recepción y almacenamiento de los residuos, pasando por los distintos tipos de hornos y las exigencias de los códigos de buena práctica de combustión, el sistema de aire de combustión y el sistema de humos. Se presentan también los distintos sistemas de depuración de los gases de combustión, y finalmente el sistema de evacuación de cenizas y escorias.El capítulo 4, La planta de tratamiento de residuos sólidos urbanos de Girona, describe los principales sistemas de la planta incineradora de Girona: la alimentación de residuos, el tipo de horno, el sistema de recuperación de energía, y el sistema de depuración de los gases de combustión Se describe también el sistema de control, la operación, los datos de funcionamiento de la planta, la instrumentación y las variables que son de interés para el control del proceso de combustión.En el capítulo 5, Técnicas utilizadas, se proporciona una visión global de los sistemas basados en el conocimiento y de los sistemas expertos. Se explican las diferentes técnicas utilizadas: redes neuronales, sistemas de clasificación, modelos cualitativos, y sistemas expertos, ilustradas con algunos ejemplos de aplicación.Con respecto a los sistemas basados en el conocimiento se analizan en primer lugar las condiciones para su aplicabilidad, y las formas de representación del conocimiento. A continuación se describen las distintas formas de razonamiento: redes neuronales, sistemas expertos y lógica difusa, y se realiza una comparación entre ellas. Se presenta una aplicación de las redes neuronales al análisis de series temporales de temperatura.Se trata también la problemática del análisis de los datos de operación mediante técnicas estadísticas y el empleo de técnicas de clasificación. Otro apartado está dedicado a los distintos tipos de modelos, incluyendo una discusión de los modelos cualitativos.Se describe el sistema de diseño asistido por ordenador para el diseño de sistemas de supervisión CASSD que se utiliza en esta tesis, y las herramientas de análisis para obtener información cualitativa del comportamiento del proceso: Abstractores y ALCMEN. Se incluye un ejemplo de aplicación de estas técnicas para hallar las relaciones entre la temperatura y las acciones del operador. Finalmente se analizan las principales características de los sistemas expertos en general, y del sistema experto CEES 2.0 que también forma parte del sistema CASSD que se ha utilizado.El capítulo 6, Resultados, muestra los resultados obtenidos mediante la aplicación de las diferentes técnicas, redes neuronales, clasificación, el desarrollo de la modelización del proceso de combustión, y la generación de reglas. Dentro del apartado de análisis de datos se emplea una red neuronal para la clasificación de una señal de temperatura. También se describe la utilización del método LINNEO+ para la clasificación de los estados de operación de la planta.En el apartado dedicado a la modelización se desarrolla un modelo de combustión que sirve de base para analizar el comportamiento del horno en régimen estacionario y dinámico. Se define un parámetro, la superficie de llama, relacionado con la extensión del fuego en la parrilla. Mediante un modelo linealizado se analiza la respuesta dinámica del proceso de incineración. Luego se pasa a la definición de relaciones cualitativas entre las variables que se utilizan en la elaboración de un modelo cualitativo. A continuación se desarrolla un nuevo modelo cualitativo, tomando como base el modelo dinámico analítico.Finalmente se aborda el desarrollo de la base de conocimiento del sistema experto, mediante la generación de reglas En el capítulo 7, Sistema de control de una planta incineradora, se analizan los objetivos de un sistema de control de una planta incineradora, su diseño e implementación. Se describen los objetivos básicos del sistema de control de la combustión, su configuración y la implementación en Matlab/Simulink utilizando las distintas herramientas que se han desarrollado en el capítulo anterior.Por último para mostrar como pueden aplicarse los distintos métodos desarrollados en esta tesis se construye un sistema experto para mantener constante la temperatura del horno actuando sobre la alimentación de residuos.Finalmente en el capítulo Conclusiones, se presentan las conclusiones y resultados de esta tesis.
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The construction industry with its nature of project delivery is very fragmented in terms of the various processes that encompass design, construction, facilities and assets management. Facilities managers are in the forefront of delivering sustainable assets management and hence further the venture for mitigation and adaptation to climate change. A questionnaire survey was conducted to establish perceptions, level of commitment and knowledge chasm in practising sustainable facilities management (FM). This has significant implications for sustainable design management, especially in a fragmented industry. The majority of questionnaire respondents indicated the importance of sustainability for their organization. Many of them stated that they reported on sustainability as part of their organization annual reporting with energy efficiency, recycling and waste reduction as the main concern for them. The overwhelming barrier for implementing sound, sustainable FM is the lack of consensual understanding and focus of individuals and organizations about sustainability. There is a knowledge chasm regarding practical information on delivering sustainable FM. Sustainability information asymmetry in design, construction and FM processes render any sustainable design as a sentiment and mere design aspiration. Skills and training provision, traditionally offered separately to designers and facilities managers, needs to be re-evaluated. Sustainability education and training should be developed to provide effective structures and processes to apply sustainability throughout the construction and FM industries coherently and as common practice.
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Climate change is one of the major challenges facing economic systems at the start of the 21st century. Reducing greenhouse gas emissions will require both restructuring the energy supply system (production) and addressing the efficiency and sufficiency of the social uses of energy (consumption). The energy production system is a complicated supply network of interlinked sectors with 'knock-on' effects throughout the economy. End use energy consumption is governed by complex sets of interdependent cultural, social, psychological and economic variables driven by shifts in consumer preference and technological development trajectories. To date, few models have been developed for exploring alternative joint energy production-consumption systems. The aim of this work is to propose one such model. This is achieved in a methodologically coherent manner through integration of qualitative input-output models of production, with Bayesian belief network models of consumption, at point of final demand. The resulting integrated framework can be applied either (relatively) quickly and qualitatively to explore alternative energy scenarios, or as a fully developed quantitative model to derive or assess specific energy policy options. The qualitative applications are explored here.
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The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises workspaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.
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The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises work-spaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.