Dissertations / Theses on the topic 'Energy techniques'

Over the last few years, the cost of energy from renewable resources, such as sunlight and wind, has declined resulting in an increasing use of Renewable Energy Sources (RES). As a result, the energy produced by RES is fed into the power grid while their share is expected to significantly increase in the future. However, RES are characterized by power fluctuations and their integration into the power grid might lead to power quality issues, e.g., imbalances. At the same time, new energy hungry devices such as heat-pumps and Electric Vehicles (EVs) become more and more popular. As a result, their demand in power, especially during peak-times, might lead to electrical grid overloads and congestions. In order to confront the new challenges, the power grid is transformed into the so-called Smart Grid. Major role in Smart Grid plays the Demand Response (DR) concept. According to DR, Smart Grid better matches energy demand and sup- ply by using energy flexibility. Energy flexibility exists in many individual prosumers (producers and/or consumers). For instance, an owner of an EV plugs-in his EV for more time than it is actually needed. Thus, the EV charging can be timely shifted. The load demanded for charging could be moved to time periods when production from wind turbines is high or away from peak-hours. Thus, RES share is increased and/or the electrical grid operation is improved. The Ph.D. project is sponsored by the Danish TotalFlex project (http://totalflex.dk). Main goal of the TotalFlex project is to design and establish a flexibility market framework where flexibility from individual prosumers, e.g., household devices, can be traded among different market actors such as Balance Responsible Parties (BRPs) and distribution system operators. In order for that to be achieved, the TotalFlex project utilizes the flex-offer concept. Based on the flex-offer concept, flexibility from individual prosumers is captured and represented by a generic model. However, the flexible loads from individual prosumers capture very small energy amounts and thus cannot be directly traded in the market. Therefore, aggregation becomes essential. The Ph.D. project focuses on developing aggregation techniques for energy flexibilities that will provide the opportunity to individual prosumers to participate in such a flexibility market. First, the thesis introduces several flexibility measurements in order to quantify the flexibility captured by the flex-offer model and compare flex- offers among each other, both on an individual and on an aggregated level. Flexibility is both the input and the output of the aggregation techniques. Aggregation techniques aggregate energy flexibility to achieve their goals and, at the same time, they try to retain as much flexibility as possible to be traded in the market. Thus, second, the thesis describes base-line flex-offer aggregation techniques and presents balance aggregation techniques that focus on balancing out energy supply and demand. Third, since there are cases where electrical grid congestions occur, the thesis presents two constraint-based aggregation techniques. The techniques efficiently aggregate large amounts of flex-offers taking into account physical constraints of the electrical grid. The produced aggregated flex-offers are still flexible and when scheduled, a normal grid operation is achieved. Finally, the thesis examines the financial benefits of the aggregation techniques. It introduces flex-offer aggregation techniques that take into account real market technical requirements. As a result, individual small flexible loads can be indirectly traded in the energy market through aggregation. The proposed aggregation techniques for energy flexibilities can con- tribute to the use of flexibility in the Smart Grid in both current and future market frameworks. The designed techniques can improve the services offered to the prosumers and avoid the very costly upgrades of the distribution network.
Gennem de senere år er prisen faldet på energi fra vedvarende energikilder såsom sollys og vind, hvilket har medført et stigende forbrug af vedvarende energi. Dette har resulteret i, at energi, der produceret af vedvarende energi, sendes ud i elnettet og andelen forventes at stige markant i fremtiden. Vedvarende energi er imidlertid karakteriseret af effektsvingninger, og integrationen i elnettet kan føre til kvalitetsproblemer med strømmen som for eksempel uligevægt. Samtidig bliver enheder, der sluger vedvarende energi såsom varmepumper og elektriske køretøjer, mere og mere populære. Dette resulterer i, at efterspørgslen på energi, især i spidsbelastede situationer, kan medføre overbelastning og trængsel på elnettet. For at konfrontere de nye udfordringer bliver elnettet ændret til et såkaldt Smart Grid. Konceptet om udbud og efterspørgsel Demand Response (DR) spiller her en meget stor rolle. Ifølge DR, imødegår Smart Grid bedre udbud og efterspørgsel af energi ved at bruge fleksibel energi. Fleksibel energi eksisterer i mange individuelle producenter og/eller forbrugere. For eksempel tilslutter en ejer af et elektrisk køretøj sit køretøj i mere tid end det rent faktisk er nødvendigt. På denne måde kan tidspunktet for opladningen ændres rettidigt. Belastningen, der kræves for opladning, kunne flyttes til perioder, hvor produktion fra vindmøller er høj eller væk fra de spidsbelastede tidspunkter. Således øges vedvarende energi’ andel og/eller elnettets drift er forbedret. Dette Ph.D. projekt er sponsoreret af det danske TotalFlex projekt (http://totalflex.dk). TotalFlex’ formål er at designe og etablere et fleksibelt elmarkedsystem, hvor fleksibilitet fra individuelle producent og/ eller forbruger f.eks. husholdningsenheder kan blive udvekslet mellem forskellige markedsaktører såsom balanceansvarlige parter og eldistributionsnettets operatører. For at opnå dette, udnytter TotalFlex flex-offer konceptet. Baseret på konceptet om flex-offer, bliver fleksibilitet fra individuelle prosumers fanget og repræsenteret i en generisk model. Fleksible belastninger fra de individuelle prosumers fanger imidlertid kun meget små energimængder og kan ikke udveksles direkte på markedet. Derfor bliver aggregering essentielt. Ph.D. projektet fokuserer på at udvikle aggregering-steknikker for energifleksibilitet, der kan give individuelle prosumers mulighed for at deltage i et sådant fleksibilitetsmarked. Først vil afhandligen introducere adskillige fleksibilitetsmålinger for at kvantificere fleksibiliteten, der fanges af flex-offer modellen og sammenligne flex-offer med hinanden både på et individuelt og et aggregeret niveau. Input og output af aggregeringsteknikker er fleksibilitet. Aggregeringsteknikker samler energifleksibilitet for at opnå dets mål og forsøger på samme tid at beholde så meget fleksibilitet som muligt til at blive udvekslet på markedet. Herpå forsøger afhandligen for det andet at beskrive basis flexoffer aggregeringsteknikker og præsenterer balance-aggregeringsteknikker, der fokuserer på at afbalancere energiudbud og -efterspørgsel. Siden der er situationer, hvor overbelastninger af elnettet forekommer, præsenterer afhandlingen for det tredje, to begrænsningsbaserede aggregeringsteknikker. Teknikkerne samler effektivt store mængder af flex-offers og tager samtidig hensyn til fysiske begrænsninger i elnettet. De producerede, samlede flexoffers er stadig fleksible og efter det er planlagt, opnås et normaltfungerende net. Til slut vil afhandlingen undersøge de økonomiske fordele ved aggregeringsteknikkerne. Den introducerer flex-offer aggregeringsteknikkerne, der tager højde for de reelle, tekniske krav, der er på markedet. Resultatet kan være, at individuelle små fleksible belastninger indirekte kan udveksles på energimarkedet gennem aggregering. De foreslåede aggregeringsteknikker til energi-fleksibilitet kan bidrage til brug af fleksibilitet i Smart Grid i både nuværende og fremtidige markedsrammer. De designede teknikker kan forbedre de tilbudte ydelser til prosumers og undgå de meget dyre opgraderinger af distributionsnetværk
Durante los últimos años, la bajada en el precio de la energía procedente de fuentes renovables, tales como luz solar y eólica, ha resultado en un aumento del uso de este tipo de recursos de Energía Renovables (ER). Como consecuencia de este aumento, la energía producida a través de ER es inyectada en la red eléctrica y se espera que la proporción de energía suministrada a la red crezca significativamente en los próximos años. Sin embargo, las ER se caracterizan por ser muy fluctuantes y su integración en la red eléctrica podría acarrear problemas de calidad, como por ejemplo desequilibrios energéticos. Al mismo tiempo, nuevos dispositivos de alto consumo de energía, como bombas de calor y vehículos eléctricos, son cada vez mas populares y la alta demanda de estos, especialmente en horas puntas, puede crear sobrecargas y congestiones en la red. Para afrontar estos restos, la red eléctrica se transforma en la llamada Red Inteligente, dónde el concepto de respuesta a la demanda juega un papel. Esta thesis de doctorado está patrocinada por el proyecto danés TotalFlex (http://totalflex.dk). El objetivo principal de este proyecto es diseñar y establecer el marco de flexibilidad de mercado, dónde la flexibilidad de productores/consumidores, por ejemplo los dispositivos del hogar, pueda ser comercializada entre los diferentes actores del mercado como las comercializadoras de electricidad y los operadores de sistemas de distribución. Para lograr este propósito, el proyecto TotalFlex utiliza el concepto flex-offer flexibilidad en la oferta. Basado en el concepto flex-offer, la flexibilidad de consumidores y productores individuales es capturada y representada a través de un modelo genérico. Sin embargo, las cargas flexibles de estos individuos producen pequeñas cantidades de energía y, por lo tanto, no pueden ser directamente negociadas en el mercado. Esto significa que la agregación de esta energía es esencial. Este Ph.D está enfocado desarrollo de técnicas de agrega para que permitirán a productores y consumidores individuales participar en dicha. En primer lugar, esta tesis introduce medidas de flexibilidad con la finalidad de cuantificar la flexibilidad calculada por el modelo flex-offer y comparar las diferentes ofertas entre ellas, tanto a nivel individual como agregado. Flexibilidad es tanto la entrada como la salida de las técnicas de agregado, las cuáles agregan flexibilidad energética para lograr sus objetivos y, al mismo tiempo, retener la máxima flexibilidad para comerciarla en el mercado. En segundo lugar, la tesis describe la base de las tecnicas de agregado flex-offer y presenta técnicas de que se enfocan en un balance entre la oferta y la demanda energética. Tercero, dado que existen casos dónde se producen congestiones en la red eléctrica, la tesis presenta tecnicas de agregado basadas en restricciones. Dichas técnicas agregan grandes cantidades de flex-offers considerando restricciones físicas de la red eléctrica. Las flexoffers agregadas que se producen son aún flexibles y, cuando se programan, se logra una operación normal de red. Por último, en la tesis se examina los beneficios económicos de las técnicas agregadas, introduciendo técnicas de agregado flex-offer que tienen en cuenta los requisitos técnicos del mercado real. Como resultado, las pequeñas cargas individuales y flexibles pueden ser indirectamente negociadas en el mercado energético a través de la agregación. Las técnicas de agregado propuestas para favorecer la flexibildad energética puede contribuir al uso de flexibilidad en la red inteligente tanto en el presente como en el futuro. Mejorar los servicios ofrecidos a consumidores y productores así como evitar las costosas actualizaciones de la red de distribución.

The ongoing process of deregulation in energy markets changes the market from a monopoly into a complex one, in which large utilities and independent power producers are no longer suppliers with guaranteed returns but enterprisers which have to compete. This competence has forced utilities to improve their efficiency. In effect, they must still manage the challenges of physical delivery while operating in a complex market characterized by significant volatility, volumetric uncertainty and credit risk. In such an environment, risk management gains more importance than ever. In order to manage risk, first it must be measured and then this quantified risk must be utilized optimally. Using stochastic programming to construct a model for an energy company in liberalized markets is useful since it provides a generic framework to model the uncertainties and enable decisions that will perform well. However, the resulting stochastic programming problem is a large-scale one and decomposition techniques are needed to solve them.

The emerging general purpose graphics processing units (GPGPU) computing has tremendously speeded up a great variety of commercial and scientific applications. The GPUs have become prevalent accelerators in current high performance clusters. Though the computational capacity per Watt of the GPUs is much higher than that of the CPUs, the hybrid GPU clusters still consume enormous power. To conserve energy on this kind of clusters is of critical significance. In this thesis, we seek energy conservative computing on the GPU accelerated servers. We introduce our studies as follows. First, we dissect the GPU memory hierarchy due to the fact that most of the GPU applications are suffering from the GPU memory bottleneck. We find that the conventional CPU cache models cannot be applied on the modern GPU caches, and the microbenchmarks to study the conventional CPU cache become invalid for the GPU. We propose the GPU-specified microbenchmarks to examine the GPU memory structures and properties. Our benchmark results verify that the design goal of the GPU has transformed from pure computation performance to better energy efficiency. Second, we investigate the impact of dynamic voltage and frequency scaling (DVFS), a successful energy management technique for CPUs, on the GPU platforms. Our experimental results suggest that GPU DVFS is still promising in conserving energy, but the patterns to save energy strongly differ from those of the CPU. Besides, the effect of GPU DVFS depends on the individual application characteristics. Third, we derive the GPU DVFS power and performance models from our experimental results, based on which we find the optimal GPU voltage and frequency setting to minimize the energy consumption of a single GPU task. We then study the problem of scheduling multiple tasks on a hybrid CPU-GPU cluster to minimize the total energy consumption by GPU DVFS. We design an effective offline scheduling algorithm which can reduce the energy consumption significantly. At last, we combine the GPU DVFS and dynamic resource sleep (DRS), another energy management technique, to further conserve the energy, for the online task scheduling on hybrid clusters. Though the idle energy consumption increases significantly compared to the offline problem, our online scheduling algorithm still achieves more than 30% of energy conservation with appropriate runtime GPU DVFS readjustments.

Mobile data offloading has been proposed as a solution for the network congestion problem that is continuously aggravating due to the increase in mobile data demand. The concept of offloading refers to the exploitation of network heterogeneity with the objective to mitigate the load of the cellular network infrastructure. In this thesis a multicast protocol for short range networks that exploits the characteristics of physical layer network coding is presented. In the proposed protocol, named CooPNC, a novel cooperative approach is provided that allows collision resolutions with the use of an indirect inter-network cooperation scheme. Through this scheme, a reliable multicast protocol for partially overlapping short range networks with low control overhead is provided. It is shown that with CooPNC, higher throughput and energy efficiency are achieved, while it presents lower delay compared to state-of-the-art multicast protocols. A detailed description of the proposed protocol is provided, with a simple scenario of overlapping networks and also for a generalised scalable scenario. Through mathematical analysis and simulations it is proved that CooPNC presents significant performance gains compared to other state-of-the-art multicast protocols for short range networks. In order to reveal the performance bounds of Physical Layer Network Coding, the so-called Cross Network is investigated under diverse Network Coding (NC) techniques. The impact of Medium Access Control (MAC) layer fairness on the throughput performance of the network is provided, for the cases of pure relaying, digital NC with and without overhearing and physical layer NC with and without overhearing. A comparison among these techniques is presented and the throughput bounds, caused by MAC layer limitations, are discussed. Furthermore, it is shown that significant coding gains are achieved with digital and physical layer NC and the energy efficiency performance of each NC case is presented, when applied on the Cross Network.In the second part of this thesis, the uplink offloading using IP Flow Mobility (IFOM) is also investigated. IFOM allows a LTE mobile User Equipment (UE) to maintain two concurrent data streams, one through LTE and the other through WiFi access technology, that presents uplink limitations due to the inherent fairness design of IEEE 802.11 DCF. To overcome these limitations, a weighted proportionally fair bandwidth allocation algorithm is proposed, regarding the data volume that is being offloaded through WiFi, in conjunction with a pricing-based rate allocation algorithm for the rest of the data volume needs of the UEs that are transmitted through the LTE uplink. With the proposed approach, the energy efficiency of the UEs is improved, and the offloaded data volume is increased under the concurrent use of access technologies that IFOM allows. In the weighted proportionally fair WiFi bandwidth allocation, both the different upload data needs of the UEs, along with their LTE spectrum efficiency are considered, and an access mechanism is proposed that improves the use of WiFi access in uplink offloading. In the LTE part, a two-stage pricing-based rate allocation is proposed, under both linear and exponential pricing approaches, with the objective to satisfy all offloading UEs regarding their LTE uplink access. The existence of a malicious UE is also considered that aims to exploit the WiFi bandwidth against its peers in order to upload less data through the energy demanding LTE uplink and a reputation based method is proposed to combat its selfish operation. This approach is theoretically analysed and its performance is evaluated, regarding the malicious and the truthful UEs in terms of energy efficiency. It is shown that while the malicious UE presents better energy efficiency before being detected, its performance is significantly degraded with the proposed reaction method.
La derivación del tráfico de datos móviles (en inglés data offloading) ha sido propuesta como una solución al problema de la congestión de la red, un problema que empeora continuamente debido al incremento de la demanda de datos móviles. El concepto de offloading se entiende como la explotación de la heterogeneidad de la red con el objetivo de mitigar la carga de la infraestructura de las redes celulares. En esta tesis se presenta un protocolo multicast para redes de corto alcance (short range networks) que explota las características de la codificación de red en la capa física (physical layer network coding). En el protocolo propuesto, llamado CooPMC, se implementa una solución cooperativa que permite la resolución de colisiones mediante la utilización de un esquema indirecto de cooperación entre redes. Gracias a este esquema, se consigue un protocolo multicast fiable i con poco overhead de control para redes de corto alcance parcialmente solapadas. Se demuestra que el protocolo CooPNC consigue una mayor tasa de transmisión neta (throughput) y una mejor eficiencia energética, a la vez que el retardo se mantiene por debajo del obtenido con los protocolos multicast del estado del arte. La tesis ofrece una descripción detallada del protocolo propuesto, tanto para un escenario simple de redes solapadas como también para un escenario general escalable. Se demuestra mediante análisis matemático y simulaciones que CooPNC ofrece mejoras significativas en comparación con los protocolos multicast para redes de corto alcance del estado del arte. Con el objetivo de encontrar los límites de la codificación de red en la capa física (physical layer network coding), se estudia el llamado Cross Network bajo distintas técnicas de Network Coding (NC). Se proporciona el impacto de la equidad (fairness) de la capa de control de acceso al medio (Medium Access Control, MAC), para los casos de repetidor puro (pure relaying), NC digital con y sin escucha del medio, y NC en la capa física con y sin escucha del medio. En la segunda parte de la tesis se investiga el offloading en el enlace ascendente mediante IP Flow Mobility (IFOM). El IFOM permite a los usuarios móviles de LTE mantener dos flujos de datos concurrentes, uno a través de LTE y el otro a través de la tecnología de acceso WiFi, que presenta limitaciones en el enlace ascendente debido a la equidad (fairness) inherente del diseño de IEEE 802.11 DCF. Para superar estas limitaciones, se propone un algoritmo proporcional ponderado de asignación de banda para el volumen de datos derivado a través de WiFi, junto con un algoritmo de asignación de tasa de transmisión basado en pricing para el volumen de datos del enlace ascendente de LTE. Con la solución propuesta, se mejora la eficiencia energética de los usuarios móviles, y se incrementa el volumen de datos que se pueden derivar gracias a la utilización concurrente de tecnologías de acceso que permite IFOM. En el algoritmo proporcional ponderado de asignación de banda de WiFi, se toman en consideración tanto las distintas necesidades de los usuarios en el enlace ascendente como su eficiencia espectral en LTE, y se propone un mecanismo de acceso que mejora el uso de WiFi para el tráfico derivado en el enlace ascendente. En cuanto a la parte de LTE, se propone un algoritmo en dos etapas de asignación de tasa de transmisión basada en pricing (con propuestas de pricing exponencial y lineal) con el objetivo de satisfacer el enlace ascendente de los usuarios en LTE. También se contempla la existencia de usuarios maliciosos, que pretenden utilizar el ancho de banda WiFi contra sus iguales para transmitir menos datos a través del enlace ascendente de LTE (menos eficiente energéticamente). Para ello se propone un método basado en la reputación que combate el funcionamiento egoísta (selfish).

ABSTRACT Our environment is an asset to be managed carefully and is not an expendable resource to be taken for granted. The main original contribution of this thesis is in formulating intelligent techniques and simulating case studies to demonstrate the significance of the present approach for achieving a low carbon economy. Energy boosts crop production, drives industry and increases employment. Wise energy use is the first step to ensuring sustainable energy for present and future generations. Energy services are essential for meeting internationally agreed development goals. Energy management system lies at the heart of all infrastructures from communications, economy, and society’s transportation to the society. This has made the system more complex and more interdependent. The increasing number of disturbances occurring in the system has raised the priority of energy management system infrastructure which has been improved with the aid of technology and investment; suitable methods have been presented to optimize the system in this thesis. Since the current system is facing various problems from increasing disturbances, the system is operating on the limit, aging equipments, load change etc, therefore an improvement is essential to minimize these problems. To enhance the current system and resolve the issues that it is facing, smart grid has been proposed as a solution to resolve power problems and to prevent future failures. This thesis argues that smart grid consists of computational intelligence and smart meters to improve the reliability, stability and security of power. In comparison with the current system, it is more intelligent, reliable, stable and secure, and will reduce the number of blackouts and other failures that occur on the power grid system. Also, the thesis has reported that smart metering is technically feasible to improve energy efficiency. In the thesis, a new technique using wavelet transforms, floating point genetic algorithm and artificial neural network based hybrid model for gaining accurate prediction of short-term load forecast has been developed. Adopting the new model is more accuracy than radial basis function network. Actual data has been used to test the proposed new method and it has been demonstrated that this integrated intelligent technique is very effective for the load forecast. Choosing the appropriate algorithm is important to implement the optimization during the daily task in the power system. The potential for application of swarm intelligence to Optimal Reactive Power Dispatch (ORPD) has been shown in this thesis. After making the comparison of the results derived from swarm intelligence, improved genetic algorithm and a conventional gradient-based optimization method, it was concluded that swam intelligence is better in terms of performance and precision in solving optimal reactive power dispatch problems.

La récupération d'énergie par élément piézoélectrique est une technique prometteuse pour les futurs systèmes électroniques nomades autoalimentés. L'objet de ce travail est d’analyser des approches simples et agiles d’optimisation de la puissance produite par un générateur piézoélectrique. D'abord le problème de l’optimisation de l’impédance de charge d’un générateur piézoélectrique sismique est posé. Une analyse du schéma équivalent global de ce générateur a été menée sur la base du schéma de Mason. Il est démontré que la puissance extraite avec une charge complexe adaptée puisse être constante quelle que soit la fréquence et que de plus elle est égale à la puissance extraite avec la charge résistive adaptée du même système sans pertes. Il est montré toutefois que la sensibilité de cette adaptation à la valeur de la réactance de la charge la rend difficilement réaliste pour une application pratique. Une autre solution pour améliorer l’énergie extraite est de considérer un réseau de générateurs positionnés en différents endroits d’une structure. Des simulations sont proposées dans une configuration de récupération d’énergie de type directe sur une plaque encastrée. Les générateurs piézoélectriques, associés à la technique SSHI, ont été reliés selon différentes configurations. Les résultats attestent que l’énergie produite ne dépend pas de façon critique de la manière dont sont connectés les éléments. Toutefois l’utilisation d’un seul circuit SSHI pour l’ensemble du réseau dégrade l’énergie extraite du fait des interactions entre les trop nombreuses commutations. Enfin une nouvelle approche non-linéaire est étudiée qui permet l’optimisation de l’énergie extraite tout en gardant une grande simplicité et des possibilités d’auto alimentation. Cette technique appelée S3H pour « Synchronized Serial Switch Harvesting » n’utilise pas d’inductance et consiste en un simple interrupteur en série avec l’élément piézoélectrique. La puissance récupérée est le double de celle extraite par les méthodes conventionnelles et reste totalement invariante sur une large gamme de résistances de charge
Piezoelectric energy harvesting is a promising technique for battery-less miniature electronic devices. The object of this work is to evaluate simple and robust approaches to optimize the extracted power. First, a lightweight equivalent circuit derived from the Mason equivalent circuit is proposed. It’s a comprehensive circuit, which is suitable for piezoelectric seismic energy harvester investigation and power optimization. The optimal charge impedance for both the resistive load and complex load are given and analyzed. When complex load type can be implemented, the power output is constant at any excitation frequency with constant acceleration excitation. This power output is exactly the maximum power that can be extracted with matched resistive load without losses. However, this wide bandwidth optimization is not practical due to the high sensitivity the reactive component mismatch. Another approach to improve power extraction is the capability to implement a network of piezoelectric generators harvesting on various frequency nodes and different locations on a host structure. Simulations are conducted in the case of direct harvesting on a planar structure excited by a force pulse. These distributed harvesters, equipped with nonlinear technique SSHI (Synchronized Switching Harvesting on Inductor) devices, were connected in parallel, series, independently and other complex forms. The comparison results showed that the energy output didn’t depend on the storage capacitor connection method. However, only one set of SSHI circuit for a whole distributed harvesters system degrades the energy scavenging capability due to switching conflict. Finally a novel non-linear approach is proposed to allow optimization of the extracted energy while keeping simplicity and standalone capability. This circuit named S3H for “ Synchronized Serial Switch Harvesting” does not rely on any inductor and is constructed with a simple switch. The power harvested is more than twice the conventional technique one on a wide band of resistive load

The flow-induced vibration is one of the most common vibrational phenomena in the ambient environment, on which the previous studies were mainly dealing with methodologies as to how to control and reduce vibrations of objects in the flow field. Facing the growing demand of the power supply of the Internet of Things (IoT) and the Wireless Sensor Network (WSN), the energy harvesting technique utilizing multifaceted dynamic effects incurred within natural water flows is a new and meaningful area worth of further research. In this thesis, two novel strategies of the flow-induced vibration energy harvesting techniques were proposed and investigated. One is focused on the flow pattern control with the creative layouts of the bluff bodies. The other could harvest the energy from the reciprocating water flows with the utilization of the torsional vibration mode of the energy harvester. Both methods were firstly proposed and verified in this thesis. The work could not only develop the power output of the energy harvester, but also be applied in the actual hostile ambient environment. The contributions to the research provided by this thesis were made also on the optimization of the proposed topologies with numerous experimental, analytical and computational approaches. The detailed characteristics were investigated and concluded in the thesis to promote the applications of the technologies. The energy storage system was also studied and tested.

Data centers hosting internet-scale services consume megawatts of power. Mainly for cost reasons but also to appease environmental concerns, data center operators are interested to reduce their use of energy. This thesis investigates if and how hardware virtualization helps to improve the energy efficiency of modern cloud data centers. Our main motivation is to power off unused servers to save energy. The work encompasses three major parts: First, a simulation-driven analysis to quantify the benefits of known reservation times in infrastructure clouds. Virtual machines with similar expiration times are co-located to increase the probability to power down unused physical hosts. Second, we propose and prototyped a system to deliver truly on-demand cloud services. Idle virtual machines are suspended to free resources and as a first step to power off the physical server. Third, a novel block-level data synchronization tool enables fast and efficient state replication. Frequent state synchronization is necessary to prevent data unavailability: powering down a server disables access to the locally attached disks and any data stored on them. The techniques effectively reduce the overall number of required servers either through optimized scheduling or by suspending idle virtual machines. Fewer live servers translate into proportional energy savings, as the unused servers must no longer be powered.

Thesis (M. Tech. (Mech. Eng.)) -- Central University of Technology, Free state, 2010
The purpose of this research is to minimize the use of active systems in providing thermal comfort in single-family detached, middle to high income residential buildings in Bloemfontein. The typical case study house was selected according to the criteria as reviewed by Mathews et al., (1999). Measurements were taken for seven days (18 – 24 May 2009). The measurements were carried out in the winter period for Bloemfontein, South Africa. Ecolog TH1, humidity and temperature data logger was used in doing the measurements. These measurements included indoor temperatures and indoor relative humidity. Temperature swings of 8.43 ºC and thermal lag of 1 hour were observed. For the period of seven days (168 hours), the house was thermally comfortable for 84 hours. Thermal analysis for the base case house was done using Ecotect™ (building analysis software) and the simulated results were compared with the measured results. A mean bias error (MBE) of between 10.3% ≤≤11.5% was obtained on the initial calibration. The final calibration of the model yielded error between0.364% ≤≤0.365%. The final calibration model which presented a small error was adopted as the base case. Passive strategies were incorporated to the Ecotect™ model (final calibrated model) singly and in combination; then both thermal and space load simulations were obtained and compared to simulations from the original situation (base case) for assessing improvements in terms of thermal comfort and heating, ventilation and air conditioning (HVAC) energy consumption. Annual HVAC electricity savings of up to 55.2 % were obtained from incorporating passive strategies in combination. Incorporating passive strategies resulted in small improvements in thermal comfort.

Interconnection networks represent the backbone of large-scale parallel systems. In order to build ultra-scale supercomputers larger interconnection networks are being designed and deployed. As compute nodes become more energy-efficient, the interconnect is accounting for an increasing proportion of the total system energy consumption. The interconnect's energy consumption is, however, only starting to receive serious attention. Most of this power consumption is due to the interconnection links. The problem, in terms of power, of an interconnect link is that its power consumption is almost constant, whether or not it is actively exchanging data, since both ends stay active to mantain synchronization. This thesis complements ongoing efforts related to power reduction and energy proportionality of the interconnection network. The thesis contemplates two directions for power savings in the interconnection network; one is the possibility to use lower bandwidth links during the communication phases and thus save energy, while the second one addresses shifting links to low-power mode during computation phases when they are unused. To address the first one we investigate the potential benefits from MPI data compression. When compression of MPI data is possible, the reduction in link bandwidth is enabled without incurring any performance penalty. Consecutively, lower bandwidth leads to lower link energy consumption. In the past, several compression techniques have been proposed as a way to improve the performance and scalability of parallel applications. Those works have shown significant speed-ups when applying compressors to the MPI transfers of certain algorithmic kernels. However, these techniques have not seen widespread adoptation in current supercomputers. In this thesis we will show that although data compression naturally leads to improved performance, the benefit is small, for modern high-performance networks, and it varies greatly between applications. In contrast, combining data compression with switching to low-power mode preserves performance while delivering effective and consistent energy savings, in proportion with the reduction in data rate. In general, application developers view time spent in a communication as an overhead, and therefore strive to keep it at minimum. This leads to high peak bandwidth demand and latency sensitivity, but low average utilization, which provides significant opportunities for energy savings. It is therefore possible to save energy using low-power modes, but link wake-up latencies must not lead to a loss in performance. Thus, we propose a mechanism that can accurately predict when links are idle, allowing them to be switched to more power efficient mode. Our runtime system called the Pattern Prediction System (PPS) can accurately predict not only when a link will become unused but also when it will become active again, allowing links to be switched off during the idle periods and switched back on again in time to avoid incurring a significant performance degradation. Many HPC application benefit from prediction, since they have repetitive computation and communication phases. By implementing the energy-saving mechanisms inside the MPI library, existing MPI programs do not need to be modified. We also develop more advanced version of the prediction system, Self-Tuned Pattern Prediction System (SPPS) which is capable of automatically tuning to the current application communication characteristic and shaping the switching on/off of the links in the most appropriate way. The proposed compression and prediction techniques are evaluated using an event-driven simulator, which is able to replay the traces from real execution of MPI applications. Experimental results show significant energy savings in the IB links while the performance overhead due to wake-up latencies and additional computation time have negligible effects on the final application performance.
En los últimos años, el consumo de energia en la red de interconexión se esta considerando como uno de los factores que pueden condicionar la carrera hacia los sistemas Exascale. En la red de interconexion, la mayor parte de este consumo de energía se debe a los enlaces de red, cuyo consumo permanece constante independientemente de si los datos se intercambian de forma activa, dado que ambos extremos deben de permanecer activos para poder mantener la sincronización. Esta tesis complementa los esfuerzos de investigación que actualmente se estan llevando a cabo a nivel internacional con el objetivo de reducir la potencia y conseguir una proporcionalidad de consumo de energía con respecto al ancho de banda requerido en las comunicaciones. En esta tesis se contemplan dos direcciones complementarias para conseguir dichos objetivos: por un lado, la posibilidad de usar sólo el ancho de banda necesario durante las fases de comunicación; y por lo tanto usar el modo de bajo consumo durante las fases de computación en las que no se requiere de la red de interconexión. Para abordar la primera de ellas se investiga los posibles beneficios de usar compresión en los datos que se transfieren en los mensajes MPI. Cuando ello es posible, se puede realizar la comunicación con una menor necesidad de ancho de banda de los enlaces sin que necesariamente se produzca una penalizacion en el rendimiento de la aplicación. Varias técnicas de compresión han sido propuestas en la literatura con el objetivo de reducir el tiempo de comunicación y la escalabilidad de las aplicaciones paralelas. Aunque estas técnicas han mostrado un potencial importante en ciertos nucleos computacionales, su adopción en sistemas reales no se ha llevado a cabo. En esta tesis, se muestra como el uso de la compresión de datos en los mensajes MPI puede permitir una reducción en el consumo de energia, reduciendo el número de enlaces activos que son requeridos para realizar la comunicación, en proporción a la reducción de los bytes que deben de ser transferidos. En general, los desarrolladores de aplicaciones consideran el tiempo pasado en la comunicación como un gasto innecesario, y por lo tanto se esfuerzan en mantenerlo al mínimo. Esto lleva a una demanda de un ancho de banda que puede afrontar el pico de alto trafico y de una sensibilidad a la latencía, pero con una utilización mediana baja, lo que ofrece unas oportunidades significativas para el ahorro de energía. Por lo tanto, es posible ahorrar la energía apoyándose en los modos de bajo consumo, pero las latencias de reactivación de los enlaces no deben producir una pérdida en el rendimiento. En esta tesis doctoral se propone un mecanismo que permite predecir con exactitud los periodos de inactividad de los enlaces, lo que permitirá pasarlos al modo más eficiente de energía que disponga la infraestructura de red. La propuesta en esta tesis doctoral actua en tiempo de ejecución y se denomina Sistema de Predicción de Patrones (SPP). SPP permite predecir con exactitud no sólo cuando un enlace llega a ser no usado, sino también cuando se requiere de nuevo su reactivación, permitiendo que los enlaces entren en modo de bajo consumo durante los periodos de inactividad y se vuelven de nuevo activos a tiempo evitando provocar una degradación significativa en el rendimiento. Muchas aplicaciones de HPC (High-Performance Computing) pueden beneficiarse de esta predicción, ya que tienen fases de computación y de comunicación repetitivas. Mediante la implementación de los mecanismos de ahorro de energía dentro de la libreria MPI, los programas MPI existentes no requiren ninguna modificación. En la tesis, tambien desarrollamos una version más avanzada del sistema de predicción que dominamos como el Sistema de Prediccion de Patrones con Ajustes Automáticos (SPPA) que además permite ajustar de forma autónoma uno de los parámetros importantes de SPP que determina el grado de agregación de mensajes en el algoritmo de predicción

Achieving energy efficiency has recently become a key topic of networking research due to the ever-increasing power consumption and CO2 emissions generated by large data networks. This problem is becoming even more concerning and challenging given the drastic traffic increase expected over the next few years. However, the use of efficient energy-aware strategies could overturn this situation reducing the electricity consumption of Internet data transmission networks, as well as contributing to mitigate the environmental impact of other sectors. The existence of redundant network elements with high capacities is a common design practice in current network infrastructures in order to face suddenly failures or peak traffic flows. However, these additional resources remain either unused or barely used most of the time leading to an undesired energy waste. Therefore, putting into sleep mode (i.e. a low-power state) unused elements is an effective and widely-accepted strategy to decrease the consumption of data networks. In this context, SDN can be seen as an attractive solution to achieve the long-awaited energy efficiency in current communications systems, since they allow a flexible programmability suitable for this problem. This doctoral thesis tackles the problem of optimizing the power consumption in SDN through the design of energy-aware routing techniques that minimize the number of network elements required to satisfy an incoming traffic load. Different from existing related works, we focus on optimizing energy consumption in SDN with in-band control traffic in order to close this important gap in the literature and provide solutions compatible with operational backbone networks. Complementing the general aim of improving the energy efficiency in SDN, this research is also intended to cover important related features such as network performance, QoS requirements and real-time operation. Accordingly, this study gives a general perspective about the use of energy efficient routing techniques, which cover integrated routing considerations for the data and control plane traffic in SDN. By using realistic input data, significant values of switched-off links and nodes are reached, which demonstrates the great opportunity for saving energy given by our proposals. The obtained results have also validated the intrinsic trade-off between environmental and performance concerns, considering several performance indicators. These findings confirm that energy-aware routing schemes should be designed considering specific traffic requirements and performance metric bounds. Moreover, it is shown that jointly considering QoS requirements and energy awareness is an effective approach to improve, not only the power consumption, but the performance on critical parameters such as control traffic delay and blocking rate. Similarly, the proposed dynamic traffic allocation with congestion-aware rerouting is able to handle demanding traffic arrival without degrading the performance of higher priority traffic. In general, our proposals are fine-grained, easy to implement and quite balanced and effective in their results looking for a suitable and readily deployment in real-world SDN scenarios. Therefore, the conducted research and contributions reported through this document not only add to what is known about the potential of energy-aware routing techniques, but also stand as a valuable solution on the road to a sustainable networking.
L'assoliment de l'eficiència energètica s'ha convertit recentment en un tema clau de recerca de xarxes a causa dels creixents nivells de consum d'energia i emissions de CO2 generats per les xarxes de dades. Aquest problema es torna cada vegada més preocupant i desafiant, donat el dràstic augment del trànsit esperat en els propers anys. No obstant això, l'ús d'estratègies energètiques eficients podria invertir aquesta situació, reduint el consum d'electricitat de les xarxes de dades d'Internet i contribuint a mitigar l'impacte ambiental d'altres sectors. L'existència d'elements de xarxa redundants i amb grans capacitats és una pràctica de disseny habitual en les infraestructures de xarxes actuals per afrontar fallades sobtades o fluxos de trànsit més elevats. Tanmateix, aquests recursos addicionals romanen poc o gens utilitzats la major part del temps, generant un desaprofitament d'energia no desitjat. Per tant, posar en mode de repòs (és a dir, un estat de baixa potència) elements no utilitzats és una estratègia efectiva i àmpliament acceptada per disminuir el consum en xarxes de dades. En aquest context, les xarxes definides per programari (SDN) es poden considerar una solució atractiva per aconseguir l'esperada eficiència energètica en els sistemes de comunicacions actuals, ja que permeten una flexible programabilitat idònia per a aquest problema. Aquesta tesi doctoral aborda el problema d'optimitzar el consum d'energia en SDN a través del disseny de tècniques d'encaminament conscients de l'energia que minimitzen la quantitat d'elements de xarxa necessaris per satisfer una càrrega de trànsit entrant. Diferent dels treballs existents, aquesta tesi es centra a optimitzar el consum d'energia en SDN amb el control de tràfic dins de banda per tancar aquesta important bretxa en la literatura i proporcionar solucions compatibles amb xarxes troncals operatives. Complementant l'objectiu general de millorar l'eficiència energètica en SDN, aquesta recerca també pretén cobrir altres importants paràmetres relacionats, com ara el rendiment de la xarxa, els requisits de qualitat de servei (QoS) i el funcionament en temps real. En conseqüència, aquest estudi ofereix una perspectiva general sobre l'ús de tècniques d'encaminament eficients energèticament, que contempla consideracions integrades per al tràfic de dades i del pla de control en SDN. Prenent dades d'entrada realistes, es van aconseguir desconnectar significatives quantitats d'enllaços i nodes, la qual cosa demostra la gran oportunitat d'estalvi d'energia que ofereixen les nostres propostes. Els resultats obtinguts també validen el estret compromís entre les preocupacions ambientals i les qüestions de rendiment de la xarxa, considerant diversos indicadors de rendiment. Aquests resultats confirmen que els esquemes d'encaminament conscients de l'energia s'han de dissenyar tenint en compte els requisits de tràfic específics i els límits desitjats de les mètriques de rendiment. A més, es demostra que, considerant conjuntament els requisits de QoS i de l'energia necessària, és un enfocament eficaç per millorar, no només el consum d'energia, sinó també el rendiment en paràmetres crítics, com la latència del tràfic de control i la probabilitat de bloqueig. De manera semblant, l'assignació dinàmica de tràfic proposta, amb re-encaminament conscient de la congestió, permet gestionar grans volums de trànsit sense degradar el rendiment de les demandes de major prioritat. En general, les nostres propostes són precises, fàcils d'implementar i bastant equilibrades i efectives en els seus resultats, buscant un desplegament adequat i fàcil en escenaris pràctics de SDN. Per tant, la recerca realitzada i les contribucions contingudes en aquest document no només afegeixen el que es coneix sobre el potencial de les tècniques d'encaminament conscients de l'energia, sinó que també representen una valuosa solució en el camí cap a una xarxa sostenible

Augmentar l’ús d’energia provinent de fonts renovables és important en la lluita contra el canvi climàtic. No obstant, la seva implantació planteja reptes importants deguts a la manca de continuïtat en la seva generació i al desajust que existeix amb els perfils de consum. La present tesi doctoral s’emmarca en dues propostes per incrementar el rendiment dels panells fotovoltaics en l’àmbit dels sistemes de calefacció per edificis. Per una banda, el sistema integra un tanc d'emmagatzematge d'energia tèrmica, que permet emmagatzemar l'energia generada pels panells durant el dia, a fi de poder-la consumir a les hores amb més demanda. D'altra banda, el sistema també compta amb una estratègia de control predictiu, que permet pronosticar les condicions meteorològiques i les demandes de calefacció futures, per tal d'ajustar el funcionament de tot el conjunt d'elements, considerant aquesta informació. El sistema proposat ha demostrat ser efectiu en diferents tipus de clima i habitatges.
Aumentar el uso de energía procedente de fuentes renovables es importante en la lucha contra el cambio climático. No obstante, su implantación plantea retos importantes debidos a la falta de continuidad en su generación y al desajuste que existe con los perfiles de consumo. La presente tesis doctoral se enmarca en dos propuestas para incrementar el rendimiento de los paneles fotovoltaicos en el ámbito de los sistemas de calefacción para edificios. Por un lado, el sistema integra un tanque de almacenaje de energía térmica, que permite almacenar la energía generada por los paneles durante el día, a fin de poderla consumir a las horas con más demanda. Por otro lado, el sistema también cuenta con una estrategia de control predictivo, que permite pronosticar las condiciones meteorológicas y las demandas de calefacción futuras, para ajustar el funcionamiento de todo el conjunto de elementos, considerando esta información. El sistema propuesto demostró ser efectivo en distintos tipos de climas y viviendas.
To increase the use of energy that comes from renewables is important to fight against climate change. However, their deployment leads to significant challenges due to the intermittence in their generation and the mismatch between energy demand and supply. In that sense, this PhD thesis is framed in two proposals to increase the performance of photovoltaic panels in heating systems integrated in the building sector. On the one hand, the system considers a thermal energy storage tank, which allows to store the energy produced by the panels during the solar hours, in order to consume it along the peak demand periods. On the other hand, the system also takes into account a model predictive control strategy, which enables to forecast weather conditions and future heating demands, to adjust the operation of all the elements. The proposed system demonstrated a good and effective behaviour in different climate conditions and buildings.

This thesis has contributed to the design of suitable decision-making techniques for energy management in the smart grid with emphasis on energy efficiency and uncertainty analysis in two smart grid applications. First, an energy trading model among distributed microgrids (MG) is investigated, aiming to improve energy efficiency by forming coalitions to allow local power transfer within each coalition. Then, a more specific scenario is considered that is how to optimally schedule Electric Vehicles (EV) charging in a MG-like charging station, aiming to match as many as EV charging requirements with the uncertain solar energy generation. The solutions proposed in this thesis can give optimal coalition formation patterns for reduced power losses and achieve optimal performance for the charging station. First, several algorithms based on game theory are investigated for the coalition formation of distributed MGs to alleviate the power losses dissipated on the cables due to power transfer. The seller and buyer MGs can make distributed decisions whether to form a coalition with others for energy trading. The simulation results show that game theory based methods that enable cooperation yield a better performance in terms of lower power losses than a non-cooperative approach. This is because by forming local coalitions, power is transferred within a shorter distance and at a lower voltage. Thus, the power losses dissipated on the transmission lines and caused by power conversion at the transformer are both reduced. However, the merge-and-split based cooperative games have an inherent high computational complexity for a large number of players. Then, an efficient framework is established for the power loss minimization problem as a college admissions game that has a much lower computational complexity than the merge-and-split based cooperative games. The seller and buyer MGs take the role of colleges and students in turn and apply for a place in the opposite set following their preference lists and the college MGs’ energy quotas. The simulation results show that the proposed framework demonstrates a comparable power losses reduction to the merge-and-split based algorithms, but runs 700 and 18000 times faster for a network of 10 MGs and 20 MGs, respectively. Finally, the problem of EV charging using various energy sources is studied along with their impact on the charging station’s performance. A multiplier k is introduced to measure the effect of solar prediction uncertainty on the decision-making process of the station. A composite performance index (the Figure of Merit, FoM) is also developed to measure the charging station’s utility, EV users charging requirements and the penalties for turning away new arrivals and for missing charging deadlines. A two-stage admission and scheduling mechanism is further proposed to find the optimal trade-off between accepting EVs and missing charging deadlines by determining the best value of the parameter k under various energy supply scenarios. The numerical evaluations give the solution to the optimization problem and show that some of the key factors such as shorter and longer deadline urgencies of EVs charging requirements, stronger uncertainty of the prediction error, storage capacity and its initial state will not affect significantly the optimal value of the parameter k.

Les progrès technologiques ont permis le développement d'applications de capteurs sans fil. Les capteurs densément distribués impliquent le plus souvent de faibles débits de données et de faibles portées de transmission. L'efficacité énergétique demeure une contrainte importante pour la conception des réseaux de capteurs sans fil. Pour ces applications, les noeuds sont généralement déployés avec des ressources énergétiques réduites et le remplacement d'une batterie peut être coûteux. Plusieurs méthodes peuvent être utilisées pour minimiser la consommation d'énergie dans ces réseaux. Dans cette thèse, nous nous concentrons sur la couche physique et sur la réduction de la consommation d'énergie des méthodes de transmission en utilisant des modulations à faible énergie. Une première étude nous permet de déduire que pour un canal BBAG, le codage à minimum d’énergie basé sur la modulation OOK est efficace énergétiquement, mais au prix d’une efficacité spectrale réduite. Seule la puissance de transmission est considérée et la consommation des circuits électroniques n’est pas prise en compte. Ensuite, des modèles de consommation d'énergie différents sont introduits afin d’obtenir une analyse de l'efficacité énergétique de transmetteurs réalistes. Le fait que le codage à minimum d’énergie améliore l'efficacité énergétique est confirmé et les limites des circuits électroniques pratiques sont mises en évidence. Enfin, le protocole réseau est abordé par l'introduction du protocole de contrôle d'erreurs ARQ. Finalement, l'efficacité énergétique d'une télécommande autonome est améliorée en utilisant la modulation orthogonale OOK et un véritable démonstrateur est présenté
Technological advances have resulted in the development of wireless sensor applications. The densely distributed sensors, generally used for data gathering, environmental monitoring, industrial automation or surveillance, involve often low data rates and low transmission ranges. Despite the progress in software and hardware technologies, the energy efficiency is still one of the important constraints for the design of Wireless Sensor Network (WSN). For wireless sensor applications, nodes are usually deployed with reduced energy resources and without capability of battery replacement. Several techniques could be used to minimize the energy consumption of WSN. In this thesis we focus the physical layer and we propose to reduce the energy consumption by using low energy coding schemes. Firstly, a study allows us to deduce that in AWGN channel, Minimum-Energy Coding based on OOK modulation is energy efficiency, but at the price of lower spectrum efficiency. Only the transmission power is considered and the consumption of electronic circuits is not taken into account. Then, different energy consumption models are introduced to achieve energy efficiency analysis using realistic devices. The fact that Minimum-Energy coding based on OOK improves the energy efficiency performance is confirmed and the limits of practical circuits are highlighted. At last, the network protocol is addressed by introducing the ARQ error control protocol. Finally, the energy efficiency of an autonomous remote control is improved by using OOK orthogonal modulation and a real demonstrator is realized

Rapid device-miniaturization keeps on inducing challenges in building energy efficient microprocessors. As the size of the transistors continuously decreasing, more uncertainties emerge in their operations. On the other hand, integrating more and more transistors on a single chip accentuates the need to lower its supply-voltage. This dissertation investigates one of the primary device uncertainties - timing error, in microprocessor performance bottleneck in NTC era. Then it proposes various innovative techniques to exploit these opportunities to maintain processor energy efficiency, in the context of emerging challenges. Evaluated with the cross-layer methodology, the proposed approaches achieve substantial improvements in processor energy efficiency, compared to other start-of-art techniques.

Energy consumption has become one of the main design constraints in today’s integrated circuits. Techniques for energy optimization, from circuit-level up to system-level, have been intensively researched. The advent of large-scale integration with deep sub-micron technologies has led to both high power densities and high chip working temperatures. At the same time, leakage power is becoming the dominant power consumption source of circuits, due to continuously lowered threshold voltages, as technology scales. In this context, temperature is an important parameter. One aspect, of particular interest for this thesis, is the strong inter-dependency between leakage and temperature. Apart  from leakage power, temperature also has an important impact on circuit delay and, implicitly, on the frequency, mainly through its influence on carrier mobility and threshold voltage. For power-aware design techniques, temperature has become a major factor to be considered. In this thesis, we address the issue of system-level energy optimization for real-time embedded systems taking temperature aspects into consideration. We have investigated two problems in this thesis: (1) Energy optimization via temperature-aware dynamic voltage/frequency scaling (DVFS). (2) Energy optimization through temperature-aware idle time (or slack) distribution (ITD). For the above two problems, we have proposed off-line techniques where only static slack is considered. To further improve energy efficiency, we have also proposed online techniques, which make use of both static and dynamic slack. Experimental results have demonstrated that considerable improvement of the energy efficiency can be achieved by applying our temperature-aware optimization techniques. Another contribution of this thesis is an analytical temperature analysis approach which is both accurate and sufficiently fast to be used inside an energy optimization loop.

Obesity is a major growing cause of death with no effective long-term treatment apart from surgical procedures such as Roux-en-Y gastric bypass (RYGB). The sustained weight loss following surgery is thought to be due in part to the increased levels of circulating anorexigenic gut hormones such as peptide YY3-36 (PYY3-36). Peripheral administration of PYY3-36 suppresses appetite in rodents and man and represents a potential therapy for obesity however its effects on feeding are transient. Here I have characterized a long-lasting PYY3-36 analogue; PYY3-36 latrotoxin (PYY3-36 (LT)) which demonstrated greater longevity than PYY3-36 in acute feeding studies and that produced a 10% reduction in bodyweight following once daily peripheral administration in a one month chronic feeding study performed on diet induced obese mice. Manganese enhanced MRI (MEMRI) has been used previously to assess the effects of nutritional status and gut hormones on brainstem and hypothalamic neuronal activity in vivo. I revealed through the MEMRI technique that the anorexigenic hormone pancreatic polypeptide (PP) modulates hypothalamic neuronal activity in fasted mice. Following this work, I performed more in-depth MEMRI experiments that revealed differential temporal effects of PYY3-36 and PYY3-36 (LT) on hypothalamic neuronal activity in fasted mice after treatment that corresponded to the effects seen with these peptides in feeding stuides. I also performed pharmacological MEMRI studies with the food additive monosodium glutamate (MSG) and confirmed its excitatory effect on neurons of the arcuate nucleus of the hypothalamus (ARC) following peripheral administration to mice. Roux-en-Y gastric bypass has been shown to increase energy expenditure possibly via a brown adipose tissue (BAT) mediated mechanism. I performed positron emission tomography-computed tomography (PET-CT) experiments on a rodent model of RYGB. I observed no differences in the activity of BAT of RYGB animals compared to shamoperated controls, indicating means other than increased BAT activity account for the weight loss seen in this bariatric model. The work in this thesis demonstrates that long-lasting PYY3-36 analogues represent a viable obesity therapy. Furthermore, I have further developed both MEMRI and PET-CT techniques for the study of energy balance.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1996.
Includes bibliographical references (p. 99-100).
This thesis investigates potential energy savings due to the application of power managed PCS, monitors, and workstations. The basis of this effort includes electric metering of such equipment at six preliminary and one primary location, a large business office in Boston, Massachusetts. Metering there occurred over an 8 week period, using an in-line metering device, and at a resolution of one minute intervals. The results of this study show that many problems exist in the field today which prevent any energy savings from being realized. These include both software and hardware incompatibilities. It was found that either the equipment was not enabled from the beginning; that various problems caused inadvertent disabling of the energy saving features, or that lack of knowledge about specific power management techniques caused the user to intentionally disable the features. Since this work began, the EPA's Energy Star Computers and Monitors Program updated their requirements such that energy saving features are now enabled when they are shipped from the manufacturer. All computers tested in this investigation were installed before the application of this condition, which was October 1, 1995. However, many problems exist other than those remedied by this requirement, including: computers which disengage from the network environment upon entering the lowest power management levels, various software incompatibilities, problematic methods of achieving power reduction, and little to no training of users or even prior negative experiences with power managed equipment There is a need for manufacturers to develop suitable or standard methods of achieving power management In addition, computer procurement employees or users must be taught about power management methods, and must have an opportunity to voice questions or concerns to manufacturers regarding power managed equipment. More research needs to be focused on network incompatibilities. Specifically, many computers are disconnected from their network upon engaging the lowest power level. This is due to either unacceptable power management methods or "stand-alone" power manageable computers which are placed on a network. Users purchasing computers intended for network use should be informed about whether the energy saving features are compatible with their type of network. This thesis is divided into two parts, the first for PCs and the second for workstations. The primary metering site for workstations was the Massachusetts Institute of Technology, which contains both Energy Star compliant and non-compliant machines. Opportunities for energy conservation in workstations are compared and contrasted to those of desktop PCs and monitors. In addition, current and future trends in workstation manufacturing and their impacts on energy conservation are explored.
by Kristie L. Bosko.
M.S.

Battery-powered portable embedded systems have been widely used in many applications. These embedded systems have to concurrently perform a multitude of complex tasks under stringent time constraints. As these systems become more complex and incorporate more functionality, they became more power-hungry. Thus, reducing power consumption and extending battery lifespan while guaranteeing the timing constraints has became a critical aspect in designing such systems. This gives rise to three aspects of research: (i) Guaranteeing the execution of the hard real-time tasks by their deadlines, (ii) Determining the minimum voltage under which each task can be executed, and (iii) Techniques to take advantage of run-time variations in the execution times of tasks. In this research, we present techniques that address the above aspects in single and multi processor embedded systems. We study the performance of the proposed techniques on various benchmarks in terms of energy savings.

The primary outcome of this research project is the development of a methodology enabling fast automated early-stage power and energy analysis of configurable processors for system-on-chip platforms. Such capability is essential to the process of selecting energy efficient processors during design-space exploration, when potential savings are highest. This has been achieved by developing dynamic and static energy consumption models for the constituent blocks within the processors. Several optimisations have been identified, specifically targeting the most significant blocks in terms of energy consumption. Instruction encoding mechanism reduces both the energy and area requirements of the instruction cache; modifications to the multiplier unit reduce energy consumption during inactive cycles. Both techniques are demonstrated to offer substantial energy savings. The aforementioned techniques have undergone detailed evaluation and, based on the positive outcomes obtained, have been incorporated into Cascade, a system-on-chip coprocessor synthesis tool developed by Critical Blue, to provide automated analysis and optimisation of processor energy requirements. This thesis details the process of identifying and examining each method, along with the results obtained. Finally, a case study demonstrates the benefits of the developed functionality, from the perspective of someone using Cascade to automate the creation of an energy-efficient configurable processor for system-on-chip platforms.

Owing to the dramatic increase in the smart devices' users in quest of high link capacity, the design of the next generation of wireless networks will necessarily have to consider spectral and energy effciency as the key pillars. The future wireless heterogeneous cellular networks (HCNs), featuring planned base stations (BSs), overlaid with unplanned micro, pico and femto BSs, can provide substantial gains in throughput and user experience as compared to the conventional homogeneous networks. My research is focusing on developing analytical models for HCNs employing spectrum and energy efficient techinques using tools from stochastic geometry. The first work is motivated to jointly support energy sustainability and high throughput performance by integrating simultaneous information and wireless power transfer (SWIPT) with HCNs. In this work, a tractable model for joint uplink (UL) and downlink (DL) transmission in a K-tier HCN with SWIPT is developed where the mobile users (MUs) decode information as well as harvest energy in the DL. The harvested energy is then utilized for UL information transmission. The analytical expressions for the DL average received power, the DL and UL outage probabilities and average ergodic rates are derived for the system design. The UL performance of a MU is shown to be improved by increasing the fraction of the DL received power for energy harvesting in the network, whereas the energy eciency is shown to be improved with the increase in SBSs density. The second work proposed a K-tier HCNs wherein the macrocell tier comprises half duplex (HD) BSs and the small cell tiers consist of full duplex (FD) BSs. In theory, FD data transmission is capable of doubling the spectral eciency with the same amount of energy compared to that of half-duplex (HD) system. The FD communication is considered at the small cell BSs only due to their low-powered nature and ease of deployment. The performance of the proposed HCNs is evaluated in terms of the DL and UL average ergodic rates which is shown to be improved as compared to the conventional HCNs where all tiers operate in HD mode. An important challenge in HCNs with FD small cells is the decrease in coverage due to the increased interference from simultaneous DL and UL operations on the same band in FD mode. This motivates to consider massive multiuser multiple-input multiple-output (MIMO) at the macrocells, which is a promising wireless communication technology for improved coverage and cell edge performance. In the third work, HCNs with massive MIMO antennas at the macrocell BSs and FD small cell is studied. Since, UL power control further improves the coverage performance of the cell edge MUs and eciently utilize their battery, distance proportional fractional power control has been considered as well. It is shown that the link reliability and area spectral eciency of the network can be signi cantly leveraged by taking advantage of FD small cell BSs density and the number of antennas at the macrocell BSs. At the end, according to the overall picture of the research conducted, the main conclusions together with some directions for the future work are presented.

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
Includes bibliographical references (leaves 30-31).
by Daniel Aaron Hartley.
M.Eng.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 167-174).
Trends in the medical industry have created a growing demand for implantable medical devices. In particular, the need to provide medical professionals a means to continuously monitor bio-markers over long time scales with increased precision is paramount to efficient healthcare. To make medical implants more attractive, there is a need to reduce their size and power consumption. Small medical implants would allow for less invasive procedures and greater comfort for patients. The two primary limitations to the size of small medical implants are the batteries that provide energy to circuit and sensor components, and the antennas that enable wireless communication to terminals outside of the body. In this work we present energy management and low-power techniques to help solve the engineering challenges posed by using ultracapacitors for energy storage. A major problem with using any capacitor as an energy source is the fact that its voltage drops rapidly with decreasing charge. This leaves the circuit to cope with a large supply variation and can lead to energy being left on the capacitor when its voltage gets too low to supply a sufficient supply voltage for operation. Rather than use a single ultracapacitor, we demonstrate higher energy utilization by splitting a single capacitor into an array of capacitors that are progressively reconfigured as energy is drawn out. An energy management IC fabricated in 180-nm CMOS implements a stacking procedure that allows for more than 98% of the initial energy stored in the ultracapacitors to be removed before the output voltage drops unsuitably low for circuit operation. The second part of this work develops techniques for wide-input-range energy management. The first chip implementing stacking suffered an efficiency penalty by using a switchedcapacitor voltage regulator with only a single conversion ratio. In a second implementation, we introduce a better solution that preserves efficiency performance by using a multiple conversion ratio switched-capacitor voltage regulator. At any given input voltage from an ultracapcitor array, the switched-capacitor voltage regulator is configured to maximize efficiency. Fabricated in a 180-nm CMOS process, the chip achieves a peak efficiency of 90% and the efficiency does not fall below 70% for input voltages between 1.25 and 3 V.
by William R. Sanchez.
Ph.D.

Charge-scaling (CS) successive approximation register (SAR) ADC's are widely used in the design of low power electronics. Significant portions of CS-SAR ADC power are consumed by CS capacitor arrays and comparator circuits. This Dissertation presents circuit techniques to reduce the power consumption of both CS capacitor array and the latch comparator during ADC operations. The impacts of the proposed techniques on ADC accuracies are analyzed and circuit techniques are presented to address the accuracy concerns. The dissertation also presents techniques to cope with capacitor mismatches, which becomes more significant with the use of very small unit capacitors in the CS array. These techniques rely on a novel programmable CS capacitor array that allow optimally grouping the unit capacitors. Based on a 0.13um CMOS technology the proposed techniques are verified with extensive circuit simulation. Post layout simulations are done to evaluate the proposed techniques for energy efficient CS capacitor array.

This work describes three alternative processes for producing microfibrillated cellulose (MFC) in which pulp fibres are first pre-treated and then homogenized using a high-pressure homogenizer. In one process, fibre cell wall delamination was facilitated with a combined enzymatic and mechanical pre-treatment. In the two other processes, cell wall delamination was facilitated by pre-treatments that introduced anionically charged groups into the fibre wall, by means of either a carboxymethylation reaction or irreversibly attaching carboxymethyl cellulose (CMC) onto the fibres. All three processes are industrially feasible and enable production with low energy consumption. Using these methods, MFC can be produced with an energy consumption of 500–2300 kWh/tonne, which corresponds to a 91–98% reduction in energy consumption from that presented in earlier studies. These materials have been characterized in various ways and it has been demonstrated that the produced MFCs are approximately 5–30 nm wide and up to several microns long.

QC 20120928

Distillation unit is one of the most energy intensive processes and is among the major CO2 emitter in the chemical and petrochemical industries. In the quest to reduce the energy consumption and hence the environmental implications of unutilised energy, there is a strong motivation for energy saving procedures for conventional columns. Several attempts have been made to redesign and heat integrate distillation column with the aim of reducing the energy consumption of the column. Most of these attempts often involve additional capital costs in implementing. Also a number of works on applying the second law of thermodynamics to distillation column are focused on quantifying the efficiency of the column. This research aims at developing techniques of increasing the energy efficiency of the distillation column with the application of second law using the tools of advanced control and optimisation. Rigorous model from the fundamental equations and data driven models using Artificial neural network (ANN) and numerical methods (PLS, PCR, MLR) of a number of distillation columns are developed. The data for the data driven models are generated from HYSYS simulation. This research presents techniques for selecting energy efficient control structure for distillation processes. Relative gain array (RGA) and relative exergy array (REA ) were used in the selection of appropriate distillation control structures. The viability of the selected control scheme in the steady state is further validated by the dynamic simulation in responses to various process disturbances and operating condition changes. The technique is demonstrated on two binary distillation systems. In addition, presented in this thesis is optimisation procedures based on second law analysis aimed at minimising the inefficiencies of the columns without compromising the qualities of the products. ANN and Bootstrap aggregated neural network (BANN) models of exergy efficiency were developed. BANN enhances model prediction accuracy and also provides model prediction confidence bounds. The objective of the optimisation is to maximise the exergy efficiency of the column. To improve the reliability of the optimisation strategy, a modified objective function incorporating model prediction confidence bounds was presented. Multiobjective optimisation was also explored. Product quality constraints introduce a measure of penalization on the optimisation result to give as close as possible to what obtains in reality. The optimisation strategies developed were applied to binary systems, multicomponents system, and crude distillation system. The crude distillation system was fully explored with emphasis on the preflash unit, atmospheric distillation system (ADU) and vacuum distillation system (VDU). This study shows that BANN models result in greater model accuracy and more robust models. The proposed ii techniques also significantly improve the second law efficiency of the system with an additional economic advantage. The method can aid in the operation and design of energy efficient column.

Digital image feature detectors often comprise two stages of processing: an initial filtering phase and a secondary search stage. The initial filtering is designed to accentuate specific feature characteristics or suppress spurious components of the image signal. The second stage of processing involves searching the results for various criteria that will identify the locations of the image features. The local energy feature detection scheme combines the squares of the signal convolved with a pair of filters that are in quadrature with each other. The resulting local energy value is proportional to phase congruency which is a measure of the local alignment of the phases of the signals constituent Fourier components. Points of local maximum phase alignment have been shown to correspond to visual features in the image. The local energy calculation accentuates the location of many types of image features, such as lines, edges and ramps and estimates of local energy can be calculated in multidimensional image data by rotating the quadrature filters to several orientations. The second stage search criterion for local energy is to locate the points that lie along the ridges in the energy map that connect the points of local maxima. In three dimensional data the relatively higher energy values will form films between connecting laments and tendrils. This thesis examines the use of recursive spatial domain filtering to calculate local energy. A quadrature pair of filters which are based on the first derivative of the Gaussian function and its Hilbert transform, are rotated in space using a kernel of basis functions to obtain various orientations of the filters. The kernel is designed to be separable and each term is implemented using a recursive digital filter. Once local energy has been calculated the ridges and surfaces of high energy values are determined using a flooding technique. Starting from the points of local minima we perform an ablative skeletonisation of the higher energy values. The topology of the original set is maintained by examining and preserving the topology of the neighbourhood of each point when considering it for removal. This combination of homotopic skeletonisation and sequential processing of each level of energy values, results in a well located, thinned and connected tracing of the ridges. The thesis contains examples of the local energy calculation using steerable recursive filters and the ridge tracing algorithm applied to two and three dimensional images. Details of the algorithms are contained in the text and details of their computer implementation are provided in the appendices.

Dual energy X-radiography is a method first developed in the mid-1970's by which one uses the information contained in the energy spectrum of the transmitted X-ray flux through an object. With this information one can distinguish the types of materials present in a radiograph and thus allow a computer to subtract them from the image enhancing the contrast of the remaining materials. Using this method, one can see details, which would have been hidden by overlying structures of other materials such as seen in radiographs of parts, made up of mixtures of metals and composites. There is also great interest in this technique for medical imaging of the chest where images of the organs are significantly improved by subtracting the bones. However, even with the enhanced capabilities realized with this technique, the majority of X-radiography systems only measures the bulk transmitted X-ray intensity and ignores the information contained in the energy spectrum. This is due to the added expense, time requirements, and registration problems incurred using standard radiographic methods to obtain dual energy radiographs. This dissertation describes a novel method which overcomes these problems and allows one to perform inexpensive, near real time, single shot dual energy X-radiography. The work of this thesis resulted in US patent #5,742,660.

The objective of the proposed research is to devise high-performance and low-complexity signal-detection algorithms for communication systems over fading channels. They include channel equalization to combat intersymbol interference (ISI) and multiple input multiple output (MIMO) signal detection to deal with multiple access interference (MAI) from other transmit antennas. As the demand for higher data-rate and more efficiency wireless communications increases, signal detection becomes more challenging. We propose novel transmission and iterative signal-detection techniques based on energy spreading transform (EST). Different from the existing iterative methods based on the turbo principle, the proposed schemes are independent of channel coding. EST is an orthonormal that spreads a symbol energy over the symbol block in time and frequency for channel equalization; space and time for MIMO signal detection with flat fading channels; and space, time, and frequency for MIMO signal detection with frequency-selective fading channels. Due to the spreading, EST obtains diversity in the available domains for the specific application and increases the reliability of the feedback signal. Moreover, it enables iterative signal detection that has near interference-free performance only at the complexity of linear detectors. Either a hard or soft decision can be fed back to the interference-cancellation stage at the subsequent iteration. The soft-decision scheme prevents error propagation of the hard-decision scheme for a low SNR and improves the performance. We analyze the performance of the proposed techniques. Analytical and simulation results show that these schemes perform very close to the interference-free systems.

his dissertation proposes novel techniques for assigning resources of wireless networks by considering that the coverage radii are small, implying that some power consumption sinks not considered so far shouldnow be introduced, and by considering that the devices are battery-powered terminals provided with energy harvesting capabilities. In this framework, two different configurations in terms of harvesting capabilities are considered. First, we assume that the energy source is external and not controllable, e.g. solar energy. In this context, the proposed design should adapt to the energy that is currently being harvested. We also study the effect of having a finite backhaul connection that links the wireless access network with the core network. On the other hand, we propose a design in which the transmitter feeds actively the receivers with energy by transmitting signals that receivers use for recharging their batteries. In this case, the power transfer design should be carried out jointly with the power control strategy for users that receive information as both procedures, transfer of information and transfer of power, are implemented at the transmitter and make use of a common resource, i.e., power. Apart from techniques for assigning the radio resources, this dissertation develops a procedure for switching on and off base stations. Concerning this, it is important to notice that the traffic profile is not constant throughout the day. This is precisely the feature that can be exploited to define a strategy based on a dynamic selection of the base stations to be switched off when the traffic load is low, without affecting the quality experienced by the users. Thanks to this procedure, we are able to deploy smaller energy harvesting sources and smaller batteries and, thus, to reduce the cost of the network deployment. Finally, we derive some procedures to optimize high level decisions of the network operation in which variables from several layers of the protocol stack are involved. In this context, admission control procedures for deciding which user should be connected to which base station are studied, taking into account information of the average channel information, the current battery levels, etc. A multi-tier multi-cell scenario is assumed in which base stations belonging to different tiers have different capabilities, e.g., transmission power, battery size, end energy harvesting source size. A set of strategies that require different computational complexity are derived for scenarios with different user mobility requirements.
Aquesta tesis doctoral proposa tècniques per assignar els recursos disponibles a les xarxes wireless considerant que els radis de cobertura són petits, el que implica que altres fonts de consum d’energia no considerades fins al moment s’hagin d’introduir dins els dissenys, i considerant que els dispositius estan alimentats amb bateries finites i que tenen a la seva disposició fonts de energy harvesting. En aquest context, es consideren dues configuracions diferents en funció de les capacitats de l’energia harvesting. En primer lloc, s’assumirà que la font d’energia és externa i incontrolable com, per exemple, l’energia solar. Els dissenys proposats han d’adaptar-se a l’energia que s’està recol·lectant en un precís moment. En segon lloc, es proposa un disseny en el qual el transmissor és capaç d’enviar energia als receptors mitjançant senyals de radiofreqüència dissenyats per aquest fi, energia que és utilitzada per recarregar les bateries. A part de tècniques d’assignació de recursos radio, en aquesta tesis doctoral es desenvolupa un procediment dinàmic per apagar i encendre estacions base. És important notar que el perfil de tràfic no és constant al llarg del dia. Aquest és precisament el patró que es pot explotar per definir una estratègia dinàmica per poder decidir quines estaciones base han de ser apagades, tot això sense afectar la qualitat experimentada pels usuaris. Gràcies a aquest procediment, es possible desplegar fonts d'energy harvesting més petites i bateries més petites. Finalment, aquesta tesis doctoral presenta procediments per optimitzar decisions de nivell més alt que afecten directament al funcionament global de la xarxa d’accés. Per prendre aquestes decisions, es fa ús de diverses variables que pertanyen a diferents capes de la pila de protocols. En aquest context, aquesta tesis aborda el disseny de tècniques de control d’admissió d’usuaris a estacions base en entorns amb múltiples estacions base, basant-se amb la informació estadística dels canals, i el nivell actual de les bateries, entre altres. L'escenari considerat està format per múltiples estacions base, on cada estació base pertany a una família amb diferents capacitats, per exemple, potència de transmissió o mida de la bateria. Es deriven un conjunt de tècniques amb diferents costos computacionals que són d'utilitat per a poder aplicar a escenaris amb diferents mobilitats d’usuaris.

The trend for the next generation of cellular network, the Fifth Generation (5G), predicts a 1000x increase in the capacity demand with respect to 4G, which leads to new infrastructure deployments. To this respect, it is estimated that the energy consumption of ICT might reach the 51% of global electricity production by 2030, mainly due to mobile networks and services. Consequently, the cost of energy may also become predominant in the operative expenses of a Mobile Network Operator (MNO). Therefore, an efficient control of the energy consumption in 5G networks is not only desirable but essential. In fact, the energy sustainability is one of the pillars in the design of the next generation cellular networks. In the last decade, the research community has been paying close attention to the Energy Efficiency (EE) of the radio communication networks, with particular care on the dynamic switch ON/OFF of the Base Stations (BSs). Besides, 5G architectures will introduce the Heterogeneous Network (HetNet) paradigm, where Small BSs (SBSs) are deployed to assist the standard macro BS for satisfying the high traffic demand and reducing the impact on the energy consumption. However, only with the introduction of Energy Harvesting (EH) capabilities the networks might reach the needed energy savings for mitigating both the high costs and the environmental impact. In the case of HetNets with EH capabilities, the erratic and intermittent nature of renewable energy sources has to be considered, which entails some additional complexity. Solar energy has been chosen as reference EH source due to its widespread adoption and its high efficiency in terms of energy produced compared to its costs. To this end, in the first part of the thesis, a harvested solar energy model has been presented based on accurate stochastic Markov processes for the description of the energy scavenged by outdoor solar sources. The typical HetNet scenario involves dense deployments with a high level of flexibility, which suggests the usage of distributed control systems rather than centralized, where the scalability can become rapidly a bottleneck. For this reason, in the second part of the thesis, we propose to model the SBS tier as a Multi-agent Reinforcement Learning (MRL) system, where each SBS is an intelligent and autonomous agent, which learns by directly interacting with the environment and by properly utilizing the past experience. The agents implemented in each SBS independently learn a proper switch ON/OFF control policy, so as to jointly maximize the system performance in terms of throughput, drop rate and energy consumption, while adapting to the dynamic conditions of the environment, in terms of energy inflow and traffic demand. However, MRL might suffer the problem of coordination when finding simultaneously a solution among all the agents that is good for the whole system. In consequence, the Layered Learning paradigm has been adopted to simplify the problem by decomposing it in subtasks. In particular, the global solution is obtained in a hierarchical fashion: the learning process of a subtask is aimed at facilitating the learning of the next higher subtask layer. The first layer implements an MRL approach and it is in charge of the local online optimization at SBS level as function of the traffic demand and the energy incomes. The second layer is in charge of the network-wide optimization and it is based on Artificial Neural Networks aimed at estimating the model of the overall network.
Con la llegada de la nueva generación de redes móviles, la quinta generación (5G), se predice un aumento por un factor 1000 en la demanda de capacidad respecto a la 4G, con la consecuente instalación de nuevas infraestructuras. Se estima que el gasto energético de las tecnologías de la información y la comunicación podría alcanzar el 51% de la producción mundial de energía en el año 2030, principalmente debido al impacto de las redes y servicios móviles. Consecuentemente, los costes relacionados con el consumo de energía pasarán a ser una componente predominante en los gastos operativos (OPEX) de las operadoras de redes móviles. Por lo tanto, un control eficiente del consumo energético de las redes 5G, ya no es simplemente deseable, sino esencial. En la última década, la comunidad científica ha enfocado sus esfuerzos en la eficiencia energética (EE) de las redes de comunicaciones móviles, con particular énfasis en algoritmos para apagar y encender las estaciones base (BS). Además, las arquitecturas 5G introducirán el paradigma de las redes heterogéneas (HetNet), donde pequeñas BSs, o small BSs (SBSs), serán desplegadas para ayudar a las grandes macro BSs en satisfacer la gran demanda de tráfico y reducir el impacto en el consumo energético. Sin embargo, solo con la introducción de técnicas de captación de la energía ambiental, las redes pueden alcanzar los ahorros energéticos requeridos para mitigar los altos costes de la energía y su impacto en el medio ambiente. En el caso de las HetNets alimentadas mediante energías renovables, la naturaleza errática e intermitente de esta tipología de energías constituye una complejidad añadida al problema. La energía solar ha sido utilizada como referencia debido a su gran implantación y su alta eficiencia en términos de cantidad de energía producida respecto costes de producción. Por consiguiente, en la primera parte de la tesis se presenta un modelo de captación de la energía solar basado en un riguroso modelo estocástico de Markov que representa la energía capturada por paneles solares para exteriores. El escenario típico de HetNet supondrá el despliegue denso de SBSs con un alto nivel de flexibilidad, lo cual sugiere la utilización de sistemas de control distribuidos en lugar de aquellos que están centralizados, donde la adaptabilidad podría convertirse rápidamente en un reto difícilmente gestionable. Por esta razón, en la segunda parte de la tesis proponemos modelar las SBSs como un sistema multiagente de aprendizaje automático por refuerzo, donde cada SBS es un agente inteligente y autónomo que aprende interactuando directamente con su entorno y utilizando su experiencia acumulada. Los agentes en cada SBS aprenden independientemente políticas de control del apagado y encendido que les permiten maximizar conjuntamente el rendimiento y el consumo energético a nivel de sistema, adaptándose a condiciones dinámicas del ambiente tales como la energía renovable entrante y la demanda de tráfico. No obstante, los sistemas multiagente sufren problemas de coordinación cuando tienen que hallar simultáneamente una solución de forma distribuida que sea buena para todo el sistema. A tal efecto, el paradigma de aprendizaje por niveles ha sido utilizado para simplificar el problema dividiéndolo en subtareas. Más detalladamente, la solución global se consigue de forma jerárquica: el proceso de aprendizaje de una subtarea está dirigido a ayudar al aprendizaje de la subtarea del nivel superior. El primer nivel contempla un sistema multiagente de aprendizaje automático por refuerzo y se encarga de la optimización en línea de las SBSs en función de la demanda de tráfico y de la energía entrante. El segundo nivel se encarga de la optimización a nivel de red del sistema y está basado en redes neuronales artificiales diseñadas para estimar el modelo de todas las BSs

Degree awarded (2004): DScCS, Computer Science, George Washington University
A common practice to save power and energy in embedded systems is to "put to sleep" or disable parts of the hardware. The memory system consumes a significant portion of the energy budget of the overall system, so it is a natural target for energy optimization techniques. The principle of software locality makes the memory subsystem an even better choice, since all memory blocks but the ones immediately required can be disabled at any given time. This opportunity is the motivation for developing energy optimization techniques to dynamically and selectively control the power state of the different parts of the memory system. This dissertation develops a set of algorithms and techniques that can be organized into a hardware/software co-development tool to help designers apply the selective powering of memory blocks to minimize energy consumption. In data driven embedded systems, most of the data memory is used either by global static variables or by dynamic variables. Although techniques already exist for energy-aware allocation of global static arrays under certain constraints, very little work has focused on dynamic variables, which are actually more important to event driven/data driven embedded systems than their static counterparts. This dissertation addresses this gap, and extends and consolidates previous allocation techniques in a unique framework. A formal model for memory energy optimization for dynamic and global static variables and efficient algorithms for energy aware allocation of variables to memory are presented. Dependencies between generic code and data are uncovered, and this information is exploited to fine-tune a system. A framework is presented for retrieving this profile information which is then used to design energy aware allocation algorithms for dynamic variables, including heuristics for segmentation and control of the memory heap. By working at the assembly code level, these techniques can be integrated into any compiler regardless of the source language. The proposed techniques were implemented and tested against data intensive benchmarks, and experimental results indicate significant savings of up to 50% in the memory system energy consumption.
Advisory Committee: Professor Bhagirath Narahari, Professor Hyoeong-Ah Choi (Chair), Professor Rahul Simha, Professor Shmuel Rotenstreich, Professor Can E. Korman, Dr. Yul Williams

This work describes three alternative processes for producing microfibrillated cellulose (MFC; also referred to as cellulose nanofibrils, CNF) in which bleached pulp fibres are first pretreated and then homogenized using a high-pressure homogenizer. In one process, fibre cell wall delamination was facilitated by a combined enzymatic and mechanical pretreatment. In the two other processes, cell wall delamination was facilitated by pretreatments that introduced anionically charged groups into the fibre wall, by means of either a carboxymethylation reaction or irreversibly attaching carboxymethylcellulose (CMC) to the fibres. All three processes are industrially feasible and enable energy-efficient production of MFC. Using these processes, MFC can be produced with an energy consumption of 500–2300 kWh/tonne. These materials have been characterized in various ways and it has been demonstrated that the produced MFCs are approximately 5–30 nm wide and up to several microns long. The MFCs were also evaluated in a number of applications in paper. The carboxymethylated MFC was used to prepare strong free-standing barrier films and to coat wood-containing papers to improve the surface strength and reduce the linting propensity of the papers. MFC, produced with an enzymatic pretreatment, was also produced at pilot scale and was studied in a pilot-scale paper making trial as a strength agent added at the wet-end for highly filled papers.

QC 20150126

Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Lee, Hsien-Hsin S.; Committee Member: Cahtterjee,Abhijit; Committee Member: Mukhopadhyay, Saibal; Committee Member: Pande, Santosh; Committee Member: Yalamanchili, Sudhakar.

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2004.
Page 170 blank.
Includes bibliographical references (p. 165-169).
In a number of emerging applications such as wireless sensor networks, system lifetime depends on the energy efficiency of computation and communication. The key metric in such applications is the energy dissipated per function rather than traditional ones such as clock speed or silicon area. Hardware designs are shifting focus toward enabling energy-awareness, allowing the processor to be energy-efficient for a variety of operating scenarios. This is in contrast to conventional low-power design, which optimizes for the worst-case scenario. Here, three energy-quality scalable hooks are designed into a real-valued FFT processor: variable FFT length (N=128 to 1024 points), variable bit precision (8,16 bit), and variable voltage supply with variable clock frequency (VDD=1 80mV to 0.9V, and f=164Hz to 6MHz). A variable-bit-precision and variable-FFT-length scalable FFT ASIC using an off-the-shelf standard-cell logic library and memory only scales down to 1V operation. Further energy savings is achieved through ultra-low voltage-supply operation. As performance requirements are relaxed, the operating voltage supply is scaled down, possibly even below the threshold voltage into the subthreshold region. When lower frequencies cause leakage energy dissipation to exceed the active energy dissipation, there is an optimal operating point for minimizing energy consumption.
(cont.) Logic and memory design techniques allowing ultra-low voltage operation are employed to study the optimal frequency/voltage operating point for the FFT. A full-custom implementation with circuit techniques optimized for deep voltage scaling into the subthreshold regime, is fabricated using a standard CMOS 0.18[mu]m logic process and functions down to 180mV. At the optimal operating point where the voltage supply is 350mV, the FFT processor dissipates 155nJ/FFT. The custom FFT is 8x more energy-efficient than the ASIC implementation and 350x more energy-efficient than a low-power microprocessor implementation.
by Alice Wang.
Ph.D.

Seasonal changes in the daily energy expenditure (DEE) of captive northern fur seals (Callorhinus ursinus) and key components of their energy budget (cost of resting metabolism, thermoregulation, activity and growth) were examined to elucidate potential reasons for the species’ population decline in the wild. The average DEE of 6 females was 527.8 ± 65.7 kJ kg-¹ d-¹ and fluctuated seasonally (~20% greater in the fall than in the winter). Resting metabolism also changed significantly with season, and was higher in the fall (potentially due to molting or as preparation for migratory activity). While resting metabolism was the largest component of the DEE (~80% on average), it did not follow the same seasonal trend as DEE, and therefore was not the source of the seasonal variation in DEE. Cost of activity was the second major component of DEE and may explain the observed seasonal variations. Energetic costs associated with thermoregulation appeared to be negligible. The northern fur seals were thermally neutral in all seasons for all water temperatures tested (2 °C – 18 °C), except during the summer when immersed in 2 °C water. Comparing this broad thermal neutral zone to the average sea surface temperatures encountered by fur seals in the wild during annual migrations indicates that fur seals can likely exploit a large geographic area without added thermal metabolic costs. While the direct energetic costs of growth appeared to be negligible compared to DEE, the higher growth rates in the summer and elevated resting metabolism in the fall suggests that inadequate nutrition could have greater negative effects during these seasons. Two alternative proxies for measuring energy expenditure were tested and calibrated against respirometry for potential application to wild individuals. The doubly labeled water (DLW) method over-estimated DEE by 13.1 ± 16.5% compared to respirometry. In comparison, accelerometry over-estimated DEE, using fine time scale intervals of 60 and 15 min, by an average of 5.4 ± 29.3% and 13.8 ± 39.5%, respectively. Importantly, seasonal effects (and time of day for accelerometry) must be accounted for when estimating energy expenditure from measures of DLW and acceleration in free-swimming northern fur seals.

Philosophiae Doctor - PhD
Wireless sensor networks (WSNs) have become a popular research area that is widely gaining the attraction from both the research and the practitioner communities due to their wide area of applications. These applications include real-time sensing for audio delivery, imaging, video streaming, and remote monitoring with positive impact in many fields such as precision agriculture, ubiquitous healthcare, environment protection, smart cities and many other fields. While WSNs are aimed to constantly handle more intricate functions such as intelligent computation, automatic transmissions, and in-network processing, such capabilities are constrained by their limited processing capability and memory footprint as well as the need for the sensor batteries to be cautiously consumed in order to extend their lifetime. This thesis revisits the issue of the energy efficiency in sensor networks by proposing a novel clustering approach for routing the sensor readings in wireless sensor networks. The main contribution of this dissertation is to 1) propose corrective measures to the traditional energy model adopted in current sensor networks simulations that erroneously discount both the role played by each node, the sensor node capability and fabric and 2) apply these measures to a novel hierarchical routing architecture aiming at maximizing sensor networks lifetime. We propose three energy models for sensor network: a) a service-aware model that account for the specific role played by each node in a sensor network b) a sensor-aware model and c) load-balancing energy model that accounts for the sensor node fabric and its energy footprint. These two models are complemented by a load balancing model structured to balance energy consumption on the network of cluster heads that forms the backbone for any cluster-based hierarchical sensor network. We present two novel approaches for clustering the nodes of a hierarchical sensor network: a) a distanceaware clustering where nodes are clustered based on their distance and the residual energy and b) a service-aware clustering where the nodes of a sensor network are clustered according to their service offered to the network and their residual energy. These approaches are implemented into a family of routing protocols referred to as EOCIT (Energy Optimization using Clustering Techniques) which combines sensor node energy location and service awareness to achieve good network performance. Finally, building upon the Ant Colony Optimization System (ACS), Multipath Routing protocol based on Ant Colony Optimization approach for Wireless Sensor Networks (MRACO) is proposed as a novel multipath routing protocol that finds energy efficient routing paths for sensor readings dissemination from the cluster heads to the sink/base station of a hierarchical sensor network. Our simulation results reveal the relative efficiency of the newly proposed approaches compared to selected related routing protocols in terms of sensor network lifetime maximization.

Pour réduire la consommation d'énergie due aux transmissions radio dans les réseaux de capteurs sans fil, nous proposons une nouvelle approche associant les techniques de précodage MIMO et de relais, appelé précodage distribué max-dmin (DMP). Considérant une source et un relais avec une antenne chacun, et une destination disposant de deux antennes, nous déployons un système MIMO précodé virtuel 2 × 2. Dans ce contexte, nous étudions deux techniques de relais Amplify and Forward (AF) et Decode and Forward (DF). Des comparaisons en termes de taux d'erreur et d'efficacité énergétique par rapport aux systèmes plus classiques comme les codes spatio-temporels distribués ou les combinaisons à gain maximal montrent que notre système est intéressant pour des distances de transmission moyennes (à partir de 16 mètres). Toujours dans l'objectif de maximiser l'efficacité énergétique, nous proposons une allocation de puissance sur les nœuds source et relais. Pour cela, nous dérivons analytiquement les performances du système précodage distribué max-dmin selon le mode AF et DF. Enfin,pour améliorer les performances des systèmes avec décodage au relais (DF), nous proposons un nouveau récepteur (à la destination) qui tient compte des erreurs éventuelles au niveau du relais
Among various cooperative techniques aiming to reduce power consumption for transmissions between Wireless Body Area Networks (WBAN) and base stations, we present a new approach, named distributed max-dmin precoding (DMP), combining MIMO precoding techniques and relay communications. This protocol is based on the deployment of a virtual 2 × 2 max-dmin precoding over one source, one forwarding relay, both equipped with one antenna and a destination involving 2 antennas. In this context, two kinds of relaying, amplify and forward (AF) or decode and forward (DF) protocols, are investigated. The performance evaluation in terms of Bit-Error-Rate (BER) and energy efficiency are compared with non cooperative techniques and the distributed space time block code (STBC) scheme. Our investigations show that the DMP takes the advantage in terms of energy efficiency from medium transmission distances (after 10 meters). In order to maximise the energy efficiency, we propose a power allocation over the source and the relay. Thus, we derive the performance of our system, both for AF and DF, analytically. To further increase the performance of DF cooperative schemes, we also propose to design a new decoder at the destination that takes profit from side information, namely potential errors at the relay