The effect of demand, tank parameters, and pumping stations on energy use in municipal drinking water distribution systems

Two of the indicators of the UN Millennium Development Goals ensuring environmental sustainability are energy use and per capita carbon dioxide emissions. The increasing urbanization and increasing world population may require increased energy use in order to transport enough safe drinking water to communities. In addition, the increase in water use would result in increased energy consumption, thereby resulting in increased green-house gas emissions that promote global climate change. The study of multiple Municipal Drinking Water Distribution Systems (MDWDSs) that relates various MDWDS aspects--system components and properties--to energy use is strongly desirable. The understanding of the relationship between system aspects and energy use aids in energy-efficient design. In this study, components of a MDWDS, and/or the characteristics associated with the component are termed as MDWDS aspects (hereafter--system aspects). There are many aspects of MDWDSs that affect the energy usage. Three system aspects (1) system-wide water demand, (2) storage tank parameters, and (3) pumping stations were analyzed in this study. The study involved seven MDWDSs to understand the relationship between the above-mentioned system aspects in relation with energy use. A MDWDSs model, EPANET 2.0, was utilized to analyze the seven systems. Six of the systems were real and one was a hypothetical system. The study presented here is unique in its statistical approach using seven municipal water distribution systems. The first system aspect studied was system-wide water demand. The analysis involved analyzing seven systems for the variation of water demand and its impact on energy use. To quantify the effects of water use reduction on energy use in a municipal water distribution system, the seven systems were modeled and the energy usage quantified for various amounts of water conservation. It was found that the effect of water conservation on energy use was linear for all seven systems and that all the average values of all the systems' energy use plotted on the same line with a high R 2 value. From this relationship, it can be ascertained that a 20% reduction in water demand results in approximately a 13% savings in energy use for all seven systems analyzed. This figure might hold true for many similar systems that are dominated by pumping and not gravity driven. The second system aspect analyzed was storage tank(s) parameters. Various tank parameters: (1) tank maximum water levels, (2) tank elevation, and (3) tank diameter were considered in this part of the study. MDWDSs use a significant amount of electrical energy for the pumping of water from low elevations (usually a source) to higher ones (usually storage tanks). The use of electrical energy has an effect on pollution emissions and, therefore, potential global climate change as well. Various values of these tank parameters were modeled on seven MDWDSs of various sizes using a network solver and the energy usage recorded. It was found that when averaged over all seven analyzed systems (1) the reduction of maximum tank water level by 50% results in a 2% energy reduction, (2) energy use for a change in tank elevation is system specific, and (2) a reduction of tank diameter of 50% results in approximately a 7% energy savings. The third system aspect analyzed in this study was pumping station parameters. A pumping station consists of one or more pumps. The seven systems were analyzed to understand the effect of the variation of pump horsepower and the number of booster stations on energy use. It was found that adding booster stations could save energy depending upon the system characteristics. For systems with flat topography, a single main pumping station was found to use less energy. In systems with a higher-elevation neighborhood, however, one or more booster pumps with a reduced main pumping station capacity used less energy. The energy savings for the seven systems was dependent on the number of boosters and ranged from 5% to 66% for the analyzed five systems with higher elevation neighborhoods (S3, S4, S5, S6, and S7). No energy savings was realized for the remaining two flat topography systems, S1, and S2. The present study analyzed and established the relationship between various system aspects and energy use in seven MDWDSs. This aids in estimating the amount of energy savings in MDWDSs. This energy savings would ultimately help reduce Greenhouse gases (GHGs) emissions including per capita CO 2 emissions thereby potentially lowering the global climate change effect. This will in turn contribute to meeting the MDG of ensuring environmental sustainability.

Energy efficiency standard and labeling program and consumer welfare : a case of the air conditioner market in China

Improving energy efficiency is an unarguable emergent issue in developing economies and an energy efficiency standard and labeling program is an ideal mechanism to achieve this target. However, there is concern regarding whether the consumers will choose the highly energy efficient appliances because of its high price in consequence of the high cost. This paper estimates how the consumer responds to introduction of the energy efficiency standard and labeling program in China. To quantify evaluation by consumers, we estimated their consumer surplus and the benefits of products based on the estimated parameters of demand function. We found the following points. First, evaluation of energy efficiency labeling by the consumer is not monotonically correlated with the number of grades. The highest efficiency label (Label 1) is not evaluated to be no less higher than labels 2 and 3, and is sometimes lower than the least energy efficient label (Label UI). This goes against the design of policy intervention. Second, several governmental policies affects in mixed directions: the subsidies for energy saving policies to the highest degree of the labels contribute to expanding consumer welfare as the program was designed. However, the replacement for new appliances policies decreased the welfare.

Free-Form, High Energy Performance, Transparent Envelope

This article examines, from the energy viewpoint, a new lightweight, slim, high energy efficient, light-transmitting envelope system, providing for seamless, free-form designs for use in architectural projects. The research was based on envelope components already existing on the market, especially components implemented with granular silica gel insulation, as this is the most effective translucent thermal insulation there is today. The tests run on these materials revealed that there is not one that has all the features required of the new envelope model, although some do have properties that could be exploited to generate this envelope, namely, the vacuum chamber of vacuum insulated panels (VIP), the monolithic aerogel used as insulation in some prototypes, reinforced polyester barriers. By combining these three design components — the high-performance thermal insulation of the vacuum chamber combined with monolithic silica gel insulation, the free-form design potential provided by materials like reinforced polyester and epoxy resins—, we have been able to define and test a new, variable geometry, energy-saving envelope system.

Leakage and temperature aware server control for improving energy efficiency in data centers

Reducing the energy consumption for computation and cooling in servers is a major challenge considering the data center energy costs today. To ensure energy-efficient operation of servers in data centers, the relationship among computa- tional power, temperature, leakage, and cooling power needs to be analyzed. By means of an innovative setup that enables monitoring and controlling the computing and cooling power consumption separately on a commercial enterprise server, this paper studies temperature-leakage-energy tradeoffs, obtaining an empirical model for the leakage component. Using this model, we design a controller that continuously seeks and settles at the optimal fan speed to minimize the energy consumption for a given workload. We run a customized dynamic load-synthesis tool to stress the system. Our proposed cooling controller achieves up to 9% energy savings and 30W reduction in peak power in comparison to the default cooling control scheme.

Electrical energy balance contest in Solar Decathlon Europe 2012

Solar Decathlon Europe (SDE) is an international multidisciplinary competition in which 20 universityteams build and operate energy-efficient solar-powered houses. The aim of SDE is not only scientificbut also educational and divulgative, making visitors to understand the problems presented by realengineering applications and architecture. From a research perspective, the energy data gathered dur-ing the competition constitutes a very promising information for the analysis and understanding of thephotovoltaic systems, grid structures, energy balances and energy efficiency of the set of houses. Thisarticle focuses on the electrical energy components of SDE competition, the energy performance of thehouses and the strategies and behaviors followed by the teams. The rules evaluate the houses? electricalenergy self-sufficiency by looking at the electricity autonomy in terms of aggregated electrical energybalance; the temporary generation-consumption profile pattern correlation; and the use of electricityper measurable area. Although the houses are evaluated under the same climatological and consump-tion conditions, production results are very different due to the specific engineering solutions (differentelectrical topologies, presence or absence of batteries, diverse photovoltaic module solutions, etc.)

Energy Management and Optimization for Video Decoders based on Functional-oriented Reconfiguration

In recent years, the increasing sophistication of embedded multimedia systems and wireless communication technologies has promoted a widespread utilization of video streaming applications. It has been reported in 2013 that youngsters, aged between 13 and 24, spend around 16.7 hours a week watching online video through social media, business websites, and video streaming sites. Video applications have already been blended into people daily life. Traditionally, video streaming research has focused on performance improvement, namely throughput increase and response time reduction. However, most mobile devices are battery-powered, a technology that grows at a much slower pace than either multimedia or hardware developments. Since battery developments cannot satisfy expanding power demand of mobile devices, research interests on video applications technology has attracted more attention to achieve energy-efficient designs. How to efficiently use the limited battery energy budget becomes a major research challenge. In addition, next generation video standards impel to diversification and personalization. Therefore, it is desirable to have mechanisms to implement energy optimizations with greater flexibility and scalability. In this context, the main goal of this dissertation is to find an energy management and optimization mechanism to reduce the energy consumption of video decoders based on the idea of functional-oriented reconfiguration. System battery life is prolonged as the result of a trade-off between energy consumption and video quality. Functional-oriented reconfiguration takes advantage of the similarities among standards to build video decoders reconnecting existing functional units. If a feedback channel from the decoder to the encoder is available, the former can signal the latter changes in either the encoding parameters or the encoding algorithms for energy-saving adaption. The proposed energy optimization and management mechanism is carried out at the decoder end. This mechanism consists of an energy-aware manager, implemented as an additional block of the reconfiguration engine, an energy estimator, integrated into the decoder, and, if available, a feedback channel connected to the encoder end. The energy-aware manager checks the battery level, selects the new decoder description and signals to build a new decoder to the reconfiguration engine. It is worth noting that the analysis of the energy consumption is fundamental for the success of the energy management and optimization mechanism. In this thesis, an energy estimation method driven by platform event monitoring is proposed. In addition, an event filter is suggested to automate the selection of the most appropriate events that affect the energy consumption. At last, a detailed study on the influence of the training data on the model accuracy is presented. The modeling methodology of the energy estimator has been evaluated on different underlying platforms, single-core and multi-core, with different characteristics of workload. All the results show a good accuracy and low on-line computation overhead. The required modifications on the reconfiguration engine to implement the energy-aware manager have been assessed under different scenarios. The results indicate a possibility to lengthen the battery lifetime of the system in two different use-cases.

Leakage-aware cooling management for improving server energy efficiency

The computational and cooling power demands of enterprise servers are increasing at an unsustainable rate. Understanding the relationship between computational power, temperature, leakage, and cooling power is crucial to enable energy-efficient operation at the server and data center levels. This paper develops empirical models to estimate the contributions of static and dynamic power consumption in enterprise servers for a wide range of workloads, and analyzes the interactions between temperature, leakage, and cooling power for various workload allocation policies. We propose a cooling management policy that minimizes the server energy consumption by setting the optimum fan speed during runtime. Our experimental results on a presently shipping enterprise server demonstrate that including leakage awareness in workload and cooling management provides additional energy savings without any impact on performance.

BR3: a biologically inspired fish-like robot actuated by SMA-based artificial muscles

Los peces son animales, donde en la mayoría de los casos, son considerados como nadadores muy eficientes y con una alta capacidad de maniobra. En general los peces se caracterizan por su capacidad de maniobra, locomoción silencioso, giros y partidas rápidas y viajes de larga distancia. Los estudios han identificado varios tipos de locomoción que los peces usan para generar maniobras y natación constante. A bajas velocidades la mayoría de los peces utilizan sus aletas pares y / o impares para su locomoción, que ofrecen una mayor maniobrabilidad y mejor eficiencia de propulsión. A altas velocidades la locomoción implica el cuerpo y / o aleta caudal porque esto puede lograr un mayor empuje y aceleración. Estas características pueden inspirar el diseo y fabricación de una piel muy flexible, una aleta caudal mórfica y una espina dorsal no articulada con una gran capacidad de maniobra. Esta tesis presenta el desarrollo de un novedoso pez robot bio-inspirado y biomimético llamado BR3, inspirado en la capacidad de maniobra y nado constante de los peces vertebrados. Inspirado por la morfología de los peces Micropterus salmoides o también conocido como lubina negra, el robot BR3 utiliza su fundamento biológico para desarrollar modelos y métodos matemáticos precisos que permiten imitar la locomoción de los peces reales. Los peces Largemouth Bass pueden lograr un nivel increíble de maniobrabilidad y eficacia de la propulsión mediante la combinación de los movimientos ondulatorios y aletas morficas. Para imitar la locomoción de los peces reales en una contraparte artificial se necesita del análisis de tecnologías de actuación alternativos, como arreglos de fibras musculares en lugar de servo actuadores o motores DC estándar, así como un material flexible que proporciona una estructura continua sin juntas. Las aleaciones con memoria de forma (SMAs) proveen la posibilidad de construir robots livianos, que no emiten ruido, sin motores, sin juntas y sin engranajes. Asi es como un pez robot submarino se ha desarrollado y cuyos movimientos son generados mediante SMAs. Estos actuadores son los adecuados para doblar la espina dorsal continua del pez robot, que a su vez provoca un cambio en la curvatura del cuerpo. Este tipo de arreglo estructural está inspirado en los músculos rojos del pescado, que son usados principalmente durante la natación constante para la flexión de una estructura flexible pero casi incompresible como lo es la espina dorsal de pescado. Del mismo modo la aleta caudal se basa en SMAs y se modifica para llevar a cabo el trabajo necesario. La estructura flexible proporciona empuje y permite que el BR3 nade. Por otro lado la aleta caudal mórfica proporciona movimientos de balanceo y guiada. Motivado por la versatilidad del BR3 para imitar todos los modos de natación (anguilliforme, carangiforme, subcarangiforme y tunniforme) se propone un controlador de doblado y velocidad. La ley de control de doblado y velocidad incorpora la información del ángulo de curvatura y de la frecuencia para producir el modo de natación deseado y a su vez controlar la velocidad de natación. Así mismo de acuerdo con el hecho biológico de la influencia de la forma de la aleta caudal en la maniobrabilidad durante la natación constante se propone un control de actitud. Esta novedoso robot pescado es el primero de su tipo en incorporar sólo SMAs para doblar una estructura flexible continua y sin juntas y engranajes para producir empuje e imitar todos los modos de natación, así como la aleta caudal que es capaz de cambiar su forma. Este novedoso diseo mecatrónico presenta un futuro muy prometedor para el diseo de vehículos submarinos capaces de modificar su forma y nadar mas eficientemente. La nueva metodología de control propuesto en esta tesis proporcionan una forma totalmente nueva de control de robots basados en SMAs, haciéndolos energéticamente más eficientes y la incorporación de una aleta caudal mórfica permite realizar maniobras más eficientemente. En su conjunto, el proyecto BR3 consta de cinco grandes etapas de desarrollo: • Estudio y análisis biológico del nado de los peces con el propósito de definir criterios de diseño y control. • Formulación de modelos matemáticos que describan la: i) cinemática del cuerpo, ii) dinámica, iii) hidrodinámica iv) análisis de los modos de vibración y v) actuación usando SMA. Estos modelos permiten estimar la influencia de modular la aleta caudal y el doblado del cuerpo en la producción de fuerzas de empuje y fuerzas de rotación necesarias en las maniobras y optimización del consumo de energía. • Diseño y fabricación de BR3: i) estructura esquelética de la columna vertebral y el cuerpo, ii) mecanismo de actuación basado en SMAs para el cuerpo y la aleta caudal, iii) piel artificial, iv) electrónica embebida y v) fusión sensorial. Está dirigido a desarrollar la plataforma de pez robot BR3 que permite probar los métodos propuestos. • Controlador de nado: compuesto por: i) control de las SMA (modulación de la forma de la aleta caudal y regulación de la actitud) y ii) control de nado continuo (modulación de la velocidad y doblado). Está dirigido a la formulación de los métodos de control adecuados que permiten la modulación adecuada de la aleta caudal y el cuerpo del BR3. • Experimentos: está dirigido a la cuantificación de los efectos de: i) la correcta modulación de la aleta caudal en la producción de rotación y su efecto hidrodinámico durante la maniobra, ii) doblado del cuerpo para la producción de empuje y iii) efecto de la flexibilidad de la piel en la habilidad para doblarse del BR3. También tiene como objetivo demostrar y validar la hipótesis de mejora en la eficiencia de la natación y las maniobras gracias a los nuevos métodos de control presentados en esta tesis. A lo largo del desarrollo de cada una de las cinco etapas, se irán presentando los retos, problemáticas y soluciones a abordar. Los experimentos en canales de agua estarán orientados a discutir y demostrar cómo la aleta caudal y el cuerpo pueden afectar considerablemente la dinámica / hidrodinámica de natación / maniobras y cómo tomar ventaja de la modulación de curvatura que la aleta caudal mórfica y el cuerpo permiten para cambiar correctamente la geometría de la aleta caudal y del cuerpo durante la natación constante y maniobras. ABSTRACT Fishes are animals where in most cases are considered as highly manoeuvrable and effortless swimmers. In general fishes are characterized for his manoeuvring skills, noiseless locomotion, rapid turning, fast starting and long distance cruising. Studies have identified several types of locomotion that fish use to generate maneuvering and steady swimming. At low speeds most fishes uses median and/or paired fins for its locomotion, offering greater maneuverability and better propulsive efficiency At high speeds the locomotion involves the body and/or caudal fin because this can achieve greater thrust and accelerations. This can inspire the design and fabrication of a highly deformable soft artificial skins, morphing caudal fins and non articulated backbone with a significant maneuverability capacity. This thesis presents the development of a novel bio-inspired and biomimetic fishlike robot (BR3) inspired by the maneuverability and steady swimming ability of ray-finned fishes (Actinopterygii, bony fishes). Inspired by the morphology of the Largemouth Bass fish, the BR3 uses its biological foundation to develop accurate mathematical models and methods allowing to mimic fish locomotion. The Largemouth Bass fishes can achieve an amazing level of maneuverability and propulsive efficiency by combining undulatory movements and morphing fins. To mimic the locomotion of the real fishes on an artificial counterpart needs the analysis of alternative actuation technologies more likely muscle fiber arrays instead of standard servomotor actuators as well as a bendable material that provides a continuous structure without joins. The Shape Memory Alloys (SMAs) provide the possibility of building lightweight, joint-less, noise-less, motor-less and gear-less robots. Thus a swimming underwater fish-like robot has been developed whose movements are generated using SMAs. These actuators are suitable for bending the continuous backbone of the fish, which in turn causes a change in the curvature of the body. This type of structural arrangement is inspired by fish red muscles, which are mainly recruited during steady swimming for the bending of a flexible but nearly incompressible structure such as the fishbone. Likewise the caudal fin is based on SMAs and is customized to provide the necessary work out. The bendable structure provides thrust and allows the BR3 to swim. On the other hand the morphing caudal fin provides roll and yaw movements. Motivated by the versatility of the BR3 to mimic all the swimming modes (anguilliform, caranguiform, subcaranguiform and thunniform) a bending-speed controller is proposed. The bending-speed control law incorporates bend angle and frequency information to produce desired swimming mode and swimming speed. Likewise according to the biological fact about the influence of caudal fin shape in the maneuverability during steady swimming an attitude control is proposed. This novel fish robot is the first of its kind to incorporate only SMAs to bend a flexible continuous structure without joints and gears to produce thrust and mimic all the swimming modes as well as the caudal fin to be morphing. This novel mechatronic design is a promising way to design more efficient swimming/morphing underwater vehicles. The novel control methodology proposed in this thesis provide a totally new way of controlling robots based on SMAs, making them more energy efficient and the incorporation of a morphing caudal fin allows to perform more efficient maneuvers. As a whole, the BR3 project consists of five major stages of development: • Study and analysis of biological fish swimming data reported in specialized literature aimed at defining design and control criteria. • Formulation of mathematical models for: i) body kinematics, ii) dynamics, iii) hydrodynamics, iv) free vibration analysis and v) SMA muscle-like actuation. It is aimed at modelling the e ects of modulating caudal fin and body bend into the production of thrust forces for swimming, rotational forces for maneuvering and energy consumption optimisation. • Bio-inspired design and fabrication of: i) skeletal structure of backbone and body, ii) SMA muscle-like mechanisms for the body and caudal fin, iii) the artificial skin, iv) electronics onboard and v) sensor fusion. It is aimed at developing the fish-like platform (BR3) that allows for testing the methods proposed. • The swimming controller: i) control of SMA-muscles (morphing-caudal fin modulation and attitude regulation) and ii) steady swimming control (bend modulation and speed modulation). It is aimed at formulating the proper control methods that allow for the proper modulation of BR3’s caudal fin and body. • Experiments: it is aimed at quantifying the effects of: i) properly caudal fin modulation into hydrodynamics and rotation production for maneuvering, ii) body bending into thrust generation and iii) skin flexibility into BR3 bending ability. It is also aimed at demonstrating and validating the hypothesis of improving swimming and maneuvering efficiency thanks to the novel control methods presented in this thesis. This thesis introduces the challenges and methods to address these stages. Waterchannel experiments will be oriented to discuss and demonstrate how the caudal fin and body can considerably affect the dynamics/hydrodynamics of swimming/maneuvering and how to take advantage of bend modulation that the morphing-caudal fin and body enable to properly change caudal fin and body’ geometry during steady swimming and maneuvering.

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Renewable Energies and Community Associations: Providing Homeowners with Renewable Energy Options

As energy costs increase in Colorado more homeowners will need renewable energies to provide electricity, heating and cooling for their homes. Renewable energy technology and energy efficient measures have been available for decades but Homeowner Associations (HOA) has not permitted this technology into communities primarily because of aesthetics. In April 2008, House Bill 1270 was signed into law that gives homeowners the right to make their homes more energy efficient and install renewable energy generation devices. The purpose of this capstone is to enable HOAs with information on available technology and design guideline options that can be integrated into communities and thus encourage, instead of hinder, the use of renewable energy and energy efficient measures.

Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

A non-parametric data envelopment analysis approach for improving energy efficiency of grape production

Grape is one of the world's largest fruit crops with approximately 67.5 million tonnes produced each year and energy is an important element in modern grape productions as it heavily depends on fossil and other energy resources. Efficient use of these energies is a necessary step toward reducing environmental hazards, preventing destruction of natural resources and ensuring agricultural sustainability. Hence, identifying excessive use of energy as well as reducing energy resources is the main focus of this paper to optimize energy consumption in grape production.In this study we use a two-stage methodology to find the association of energy efficiency and performance explained by farmers' specific characteristics. In the first stage a non-parametric Data Envelopment Analysis is used to model efficiencies as an explicit function of human labor, machinery, chemicals, FYM (farmyard manure), diesel fuel, electricity and water for irrigation energies. In the second step, farm specific variables such as farmers' age, gender, level of education and agricultural experience are used in a Tobit regression framework to explain how these factors influence efficiency of grape farming.The result of the first stage shows substantial inefficiency between the grape producers in the studied area while the second stage shows that the main difference between efficient and inefficient farmers was in the use of chemicals, diesel fuel and water for irrigation. The use of chemicals such as insecticides, herbicides and fungicides were considerably less than inefficient ones. The results revealed that the more educated farmers are more energy efficient in comparison with their less educated counterparts. © 2013.

Spatial-spectral flexible optical networking:enabling switching solutions for a simplified and efficient SDM network platform

The traffic carried by core optical networks grows at a steady but remarkable pace of 30-40% year-over-year. Optical transmissions and networking advancements continue to satisfy the traffic requirements by delivering the content over the network infrastructure in a cost and energy efficient manner. Such core optical networks serve the information traffic demands in a dynamic way, in response to requirements for shifting of traffics demands, both temporally (day/night) and spatially (business district/residential). However as we are approaching fundamental spectral efficiency limits of singlemode fibers, the scientific community is pursuing recently the development of an innovative, all-optical network architecture introducing the spatial degree of freedom when designing/operating future transport networks. Spacedivision- multiplexing through the use of bundled single mode fibers, and/or multi-core fibers and/or few-mode fibers can offer up to 100-fold capacity increase in future optical networks. The EU INSPACE project is working on the development of a complete spatial-spectral flexible optical networking solution, offering the network ultra-high capacity, flexibility and energy efficiency required to meet the challenges of delivering exponentially growing traffic demands in the internet over the next twenty years. In this paper we will present the motivation and main research activities of the INSPACE consortium towards the realization of the overall project solution. © 2014 Copyright SPIE.

Optimizing storage and memory systems for energy and performance

Electrical energy is an essential resource for the modern world. Unfortunately, its price has almost doubled in the last decade. Furthermore, energy production is also currently one of the primary sources of pollution. These concerns are becoming more important in data-centers. As more computational power is required to serve hundreds of millions of users, bigger data-centers are becoming necessary. This results in higher electrical energy consumption. Of all the energy used in data-centers, including power distribution units, lights, and cooling, computer hardware consumes as much as 80%. Consequently, there is opportunity to make data-centers more energy efficient by designing systems with lower energy footprint. Consuming less energy is critical not only in data-centers. It is also important in mobile devices where battery-based energy is a scarce resource. Reducing the energy consumption of these devices will allow them to last longer and re-charge less frequently. Saving energy in computer systems is a challenging problem. Improving a system's energy efficiency usually comes at the cost of compromises in other areas such as performance or reliability. In the case of secondary storage, for example, spinning-down the disks to save energy can incur high latencies if they are accessed while in this state. The challenge is to be able to increase the energy efficiency while keeping the system as reliable and responsive as before. This thesis tackles the problem of improving energy efficiency in existing systems while reducing the impact on performance. First, we propose a new technique to achieve fine grained energy proportionality in multi-disk systems; Second, we design and implement an energy-efficient cache system using flash memory that increases disk idleness to save energy; Finally, we identify and explore solutions for the page fetch-before-update problem in caching systems that can: (a) control better I/O traffic to secondary storage and (b) provide critical performance improvement for energy efficient systems.

Host and network optimizations for performance enhancement and energy efficiency in data center networks

Modern data centers host hundreds of thousands of servers to achieve economies of scale. Such a huge number of servers create challenges for the data center network (DCN) to provide proportionally large bandwidth. In addition, the deployment of virtual machines (VMs) in data centers raises the requirements for efficient resource allocation and find-grained resource sharing. Further, the large number of servers and switches in the data center consume significant amounts of energy. Even though servers become more energy efficient with various energy saving techniques, DCN still accounts for 20% to 50% of the energy consumed by the entire data center. The objective of this dissertation is to enhance DCN performance as well as its energy efficiency by conducting optimizations on both host and network sides. First, as the DCN demands huge bisection bandwidth to interconnect all the servers, we propose a parallel packet switch (PPS) architecture that directly processes variable length packets without segmentation-and-reassembly (SAR). The proposed PPS achieves large bandwidth by combining switching capacities of multiple fabrics, and it further improves the switch throughput by avoiding padding bits in SAR. Second, since certain resource demands of the VM are bursty and demonstrate stochastic nature, to satisfy both deterministic and stochastic demands in VM placement, we propose the Max-Min Multidimensional Stochastic Bin Packing (M3SBP) algorithm. M3SBP calculates an equivalent deterministic value for the stochastic demands, and maximizes the minimum resource utilization ratio of each server. Third, to provide necessary traffic isolation for VMs that share the same physical network adapter, we propose the Flow-level Bandwidth Provisioning (FBP) algorithm. By reducing the flow scheduling problem to multiple stages of packet queuing problems, FBP guarantees the provisioned bandwidth and delay performance for each flow. Finally, while DCNs are typically provisioned with full bisection bandwidth, DCN traffic demonstrates fluctuating patterns, we propose a joint host-network optimization scheme to enhance the energy efficiency of DCNs during off-peak traffic hours. The proposed scheme utilizes a unified representation method that converts the VM placement problem to a routing problem and employs depth-first and best-fit search to find efficient paths for flows.