Speculation-Aware Resource Allocation for Cluster Schedulers

Real-time demand response is essential for handling the uncertainties of renewable generation. Traditionally, demand response has been focused on large industrial and commercial loads, however it is expected that a large number of small residential loads such as air conditioners, dish washers, and electric vehicles will also participate in the coming years. The electricity consumption of these smaller loads, which we call deferrable loads, can be shifted over time, and thus be used (in aggregate) to compensate for the random fluctuations in renewable generation.

In this thesis, we propose a real-time distributed deferrable load control algorithm to reduce the variance of aggregate load (load minus renewable generation) by shifting the power consumption of deferrable loads to periods with high renewable generation. The algorithm is model predictive in nature, i.e., at every time step, the algorithm minimizes the expected variance to go with updated predictions. We prove that suboptimality of this model predictive algorithm vanishes as time horizon expands in the average case analysis. Further, we prove strong concentration results on the distribution of the load variance obtained by model predictive deferrable load control. These concentration results highlight that the typical performance of model predictive deferrable load control is tightly concentrated around the average-case performance. Finally, we evaluate the algorithm via trace-based simulations.

Injection Locked Clocking and Transmitter Equalization Techniques for Chip to Chip Interconnects

Semiconductor technology scaling has enabled drastic growth in the computational capacity of integrated circuits (ICs). This constant growth drives an increasing demand for high bandwidth communication between ICs. Electrical channel bandwidth has not been able to keep up with this demand, making I/O link design more challenging. Interconnects which employ optical channels have negligible frequency dependent loss and provide a potential solution to this I/O bandwidth problem. Apart from the type of channel, efficient high-speed communication also relies on generation and distribution of multi-phase, high-speed, and high-quality clock signals. In the multi-gigahertz frequency range, conventional clocking techniques have encountered several design challenges in terms of power consumption, skew and jitter. Injection-locking is a promising technique to address these design challenges for gigahertz clocking. However, its small locking range has been a major contributor in preventing its ubiquitous acceptance.

In the first part of this dissertation we describe a wideband injection locking scheme in an LC oscillator. Phase locked loop (PLL) and injection locking elements are combined symbiotically to achieve wide locking range while retaining the simplicity of the latter. This method does not require a phase frequency detector or a loop filter to achieve phase lock. A mathematical analysis of the system is presented and the expression for new locking range is derived. A locking range of 13.4 GHz–17.2 GHz (25%) and an average jitter tracking bandwidth of up to 400 MHz are measured in a high-Q LC oscillator. This architecture is used to generate quadrature phases from a single clock without any frequency division. It also provides high frequency jitter filtering while retaining the low frequency correlated jitter essential for forwarded clock receivers.

To improve the locking range of an injection locked ring oscillator; QLL (Quadrature locked loop) is introduced. The inherent dynamics of injection locked quadrature ring oscillator are used to improve its locking range from 5% (7-7.4GHz) to 90% (4-11GHz). The QLL is used to generate accurate clock phases for a four channel optical receiver using a forwarded clock at quarter-rate. The QLL drives an injection locked oscillator (ILO) at each channel without any repeaters for local quadrature clock generation. Each local ILO has deskew capability for phase alignment. The optical-receiver uses the inherent frequency to voltage conversion provided by the QLL to dynamically body bias its devices. A wide locking range of the QLL helps to achieve a reliable data-rate of 16-32Gb/s and adaptive body biasing aids in maintaining an ultra-low power consumption of 153pJ/bit.

From the optical receiver we move on to discussing a non-linear equalization technique for a vertical-cavity surface-emitting laser (VCSEL) based optical transmitter, to enable low-power, high-speed optical transmission. A non-linear time domain optical model of the VCSEL is built and evaluated for accuracy. The modelling shows that, while conventional FIR-based pre-emphasis works well for LTI electrical channels, it is not optimum for the non-linear optical frequency response of the VCSEL. Based on the simulations of the model an optimum equalization methodology is derived. The equalization technique is used to achieve a data-rate of 20Gb/s with power efficiency of 0.77pJ/bit.

拉曼喷泉原子钟

利用拉曼光场代替喷泉原子钟的微波腔实现拉曼喷泉原子钟。将分离拉曼光场技术与冷原子喷泉技术相结合,避免了在真空腔内放置微波腔,简化了真空系统,同时还保持了很高的准确度。采用半经典理论研究了冷原子喷泉与拉曼光场的相互作用过程,得到了冉赛(Ramsey)条纹。比较了拉曼喷泉原子钟与热铯束拉曼原子钟,前者有更小的体积和功耗,其精度可能达到或超过商用小铯钟。还比较了拉曼喷泉原子钟与微波喷泉原子钟的差别,分析了光子反冲的影响,提出利用同向传播和相向传播的两台拉曼原子钟测量精细结构常数。

Distributed Load Control in Multiphase Radial Networks

The current power grid is on the cusp of modernization due to the emergence of distributed generation and controllable loads, as well as renewable energy. On one hand, distributed and renewable generation is volatile and difficult to dispatch. On the other hand, controllable loads provide significant potential for compensating for the uncertainties. In a future grid where there are thousands or millions of controllable loads and a large portion of the generation comes from volatile sources like wind and solar, distributed control that shifts or reduces the power consumption of electric loads in a reliable and economic way would be highly valuable.

Load control needs to be conducted with network awareness. Otherwise, voltage violations and overloading of circuit devices are likely. To model these effects, network power flows and voltages have to be considered explicitly. However, the physical laws that determine power flows and voltages are nonlinear. Furthermore, while distributed generation and controllable loads are mostly located in distribution networks that are multiphase and radial, most of the power flow studies focus on single-phase networks.

This thesis focuses on distributed load control in multiphase radial distribution networks. In particular, we first study distributed load control without considering network constraints, and then consider network-aware distributed load control.

Distributed implementation of load control is the main challenge if network constraints can be ignored. In this case, we first ignore the uncertainties in renewable generation and load arrivals, and propose a distributed load control algorithm, Algorithm 1, that optimally schedules the deferrable loads to shape the net electricity demand. Deferrable loads refer to loads whose total energy consumption is fixed, but energy usage can be shifted over time in response to network conditions. Algorithm 1 is a distributed gradient decent algorithm, and empirically converges to optimal deferrable load schedules within 15 iterations.

We then extend Algorithm 1 to a real-time setup where deferrable loads arrive over time, and only imprecise predictions about future renewable generation and load are available at the time of decision making. The real-time algorithm Algorithm 2 is based on model-predictive control: Algorithm 2 uses updated predictions on renewable generation as the true values, and computes a pseudo load to simulate future deferrable load. The pseudo load consumes 0 power at the current time step, and its total energy consumption equals the expectation of future deferrable load total energy request.

Network constraints, e.g., transformer loading constraints and voltage regulation constraints, bring significant challenge to the load control problem since power flows and voltages are governed by nonlinear physical laws. Remarkably, distribution networks are usually multiphase and radial. Two approaches are explored to overcome this challenge: one based on convex relaxation and the other that seeks a locally optimal load schedule.

To explore the convex relaxation approach, a novel but equivalent power flow model, the branch flow model, is developed, and a semidefinite programming relaxation, called BFM-SDP, is obtained using the branch flow model. BFM-SDP is mathematically equivalent to a standard convex relaxation proposed in the literature, but numerically is much more stable. Empirical studies show that BFM-SDP is numerically exact for the IEEE 13-, 34-, 37-, 123-bus networks and a real-world 2065-bus network, while the standard convex relaxation is numerically exact for only two of these networks.

Theoretical guarantees on the exactness of convex relaxations are provided for two types of networks: single-phase radial alternative-current (AC) networks, and single-phase mesh direct-current (DC) networks. In particular, for single-phase radial AC networks, we prove that a second-order cone program (SOCP) relaxation is exact if voltage upper bounds are not binding; we also modify the optimal load control problem so that its SOCP relaxation is always exact. For single-phase mesh DC networks, we prove that an SOCP relaxation is exact if 1) voltage upper bounds are not binding, or 2) voltage upper bounds are uniform and power injection lower bounds are strictly negative; we also modify the optimal load control problem so that its SOCP relaxation is always exact.

To seek a locally optimal load schedule, a distributed gradient-decent algorithm, Algorithm 9, is proposed. The suboptimality gap of the algorithm is rigorously characterized and close to 0 for practical networks. Furthermore, unlike the convex relaxation approach, Algorithm 9 ensures a feasible solution. The gradients used in Algorithm 9 are estimated based on a linear approximation of the power flow, which is derived with the following assumptions: 1) line losses are negligible; and 2) voltages are reasonably balanced. Both assumptions are satisfied in practical distribution networks. Empirical results show that Algorithm 9 obtains 70+ times speed up over the convex relaxation approach, at the cost of a suboptimality within numerical precision.

卫星激光通信Ⅰ链路和终端技术

卫星激光通信具有巨大的潜在应用价值, 国际上已实现高码率、小型化、轻量化和低功耗激光通信终端, 全文的第一部分即“链路和终端技术”综述了卫星激光通信的国外进展, 介绍了终端的关键技术, 讨论了终端设计思想。第二部分(另文)将讨论和介绍卫星激光通信终端地面检测和验证技术。

Sensing and Actuation from Biology to Electronics

We introduce an in vitro diagnostic magnetic biosensing platform for immunoassay and nucleic acid detection. The platform has key characteristics for a point-of-use (POU) diagnostic: portability, low-power consumption, low cost, and multiplexing capability. As a demonstration of capabilities, we use this platform for the room temperature, amplification-free detection of a 31 bp DNA oligomer and interferon-gamma (a protein relevant for tuberculosis diagnosis). Reliable assay measurements down to 100 pM for the DNA and 1 pM for the protein are demonstrated. We introduce a novel "magnetic freezing" technique for baseline measurement elimination and to enable spatial multiplexing. We have created a general protocol for adapting integrated circuit (IC) sensors to any of hundreds of commercially available immunoassay kits and custom designed DNA sequences.

We also introduce a method for immunotherapy treatment of malignant gliomas. We utilize leukocytes internalized with immunostimulatory nanoparticle-oligonucleotide conjugates to localize and retain immune cells near the tumor site. As a proof-of-principle, we develop a novel cell imaging and incubation chamber for in vitro magnetic motility experiments. We use the apparatus to demonstrate the controlled movement of magnetically loaded THP-1 leukocytes.

Finally, we introduce an IC transmitter and power ampli er (PA) that utilizes electronic digital infrastructure, sensors, and actuators to self-heal and adapt to process, dynamic, and environmental variation. Traditional IC design has achieved incredible degrees of reliability by ensuring that billions of transistors on a single IC die are all simultaneously functional. Reliability becomes increasingly difficult as the size of a transistor shrinks. Self-healing can mitigate these variations.

Diseño de un sistema para la detección y caracterización de impactos sobre estructuras.

[ES]Este documento pretende describir de manera clara y concisa la creacion de un dispositivo detector de impactos para estructuras de avion durante su transporte de muy bajo consumo, desde su concepcion como idea hasta su montaje, programacion y posterior comprobacion. El objetivo sera la culminacion exitosa del producto para mas adelante exponerlo ante posibles compradores y/o investigadores. Este dispositivo esta compuesto de tres partes, una unidad de adquisicion y adecuacion de la señal, que ser a recogida por un piezoelectrico; la unidad de inteligencia, que sera un microcontrolador programado en ensamblador mediante la herramienta MPLAB y un chip de radio, que se encargara de transmitir los datos a una unidad mas potente, lease un PC, tablet, movil...

Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 mu m). In the case of surface finish, the absolute error is well below R-a 1 mu m (average value 0.32 mu m). The present approach can be easily generalized to other grinding operations.

Avaliação do comportamento estrutural de subestações de energia elétrica com o uso do aço inoxidável.

A crescente utilização do aço inoxidável como elemento estrutural despertou o interesse de clientes, arquitetos e engenheiros nos últimos anos. Apesar do custo ainda elevado, a sua aplicação na construção civil vem substituindo outros elementos estruturais. Seja por sua alta resistência à corrosão, aumentando a relação custo benefício; sua estética, proporcionando formas cada vez mais ousadas ou; seu apelo ambiental, gerando menos resíduos no meio ambiente. As subestações representam um papel importante no fornecimento de energia. Como possuem grande complexidade para manutenção, foi escolhida a estrutura suporte de seu barramento, para o dimensionamento em aço inoxidável. Desta forma, minimizando as paradas para realização de manutenções das estruturas, possibilitando maior qualidade no fornecimento de energia elétrica. Para fins comparativos foi escolhido o projeto de uma SE existente, cuja estrutura de suporte do barramento, foi construída por treliças formadas por cantoneiras de aço carbono galvanizado. Inicialmente, o dimensionamento foi desenvolvido utilizando perfis H e I funcionando como viga-coluna para os dois tipos de aço. Num segundo momento, a estrutura foi dimensionada como treliças planas. Todos os dimensionamentos foram realizados de acordo com as prescrições normativas do EUROCODE 3. Após realização dos dimensionamentos, foram apresentadas as análises comparativas dos custos envolvidos para os tipos de aço. Abordando o investimento inicial, os gastos com manutenção ao longo da vida e os custos elétricos agregados à redução das paradas para manutenção.

Hardware reconfigurável para identificação de radionuclídeos utilizando o método de agrupamento subtrativo.

Fontes radioativas possuem radionuclídeos. Um radionuclídeo é um átomo com um núcleo instável, ou seja, um núcleo caracterizado pelo excesso de energia que está disponível para ser emitida. Neste processo, o radionuclídeo sofre o decaimento radioativo e emite raios gama e partículas subatômicas, constituindo-se na radiação ionizante. Então, a radioatividade é a emissão espontânea de energia a partir de átomos instáveis. A identificação correta de radionuclídeos pode ser crucial para o planejamento de medidas de proteção, especialmente em situações de emergência, definindo o tipo de fonte de radiação e seu perigo radiológico. Esta dissertação apresenta a aplicação do método de agrupamento subtrativo, implementada em hardware, para um sistema de identificação de elementos radioativos com uma resposta rápida e eficiente. Quando implementados em software, os algoritmos de agrupamento consumem muito tempo de processamento. Assim, uma implementação dedicada para hardware reconfigurável é uma boa opção em sistemas embarcados, que requerem execução em tempo real, bem como baixo consumo de energia. A arquitetura proposta para o hardware de cálculo do agrupamento subtrativo é escalável, permitindo a inclusão de mais unidades de agrupamento subtrativo para operarem em paralelo. Isso proporciona maior flexibilidade para acelerar o processo de acordo com as restrições de tempo e de área. Os resultados mostram que o centro do agrupamento pode ser identificado com uma boa eficiência. A identificação desses pontos pode classificar os elementos radioativos presentes em uma amostra. Utilizando este hardware foi possível identificar mais do que um centro de agrupamento, o que permite reconhecer mais de um radionuclídeo em fontes radioativas. Estes resultados revelam que o hardware proposto pode ser usado para desenvolver um sistema portátil para identificação radionuclídeos.

Algoritmos Genéticos para Síntese de Filtros Aplicados em Controle por Modo Deslizante.

Nesta Dissertação propõe-se a aplicação de algoritmos genéticos para a síntese de filtros para modular sinais de controladores a estrutura variável e modo deslizante. A modulação do sinal de controle reduz a amplitude do sinal de saída e, consequentemente, pode reduzir o consumo de energia para realizar o controle e o chattering. Esses filtros também são aplicados em sistemas que possuem incertezas paramétricas nos quais nem todas as variáveis de estado são medidas. Nesses sistemas, as incertezas nos parâmetros podem impedir que seus estados sejam estimados com precisão por observadores. A síntese desses filtros necessita da obtenção da envoltória, que é o valor máximo da norma de cada resposta impulsiva admissível no sistema. Após este passo, é sintetizado um filtro que seja um majorante para a envoltória. Neste estudo, três métodos de busca da envoltória por algoritmos genéticos foram criados. Um dos métodos é o preferido, pois apresentou os melhores resultados e o menor tempo computacional.

Modelagem Fuzzy para previsão de uma série temporal de energia elétrica.

Esta dissertação testa e compara dois tipos de modelagem para previsão de uma mesma série temporal. Foi observada uma série temporal de distribuição de energia elétrica e, como estudo de caso, optou-se pela região metropolitana do Estado da Bahia. Foram testadas as combinações de três variáveis exógenas em cada modelo: a quantidade de clientes ligados na rede de distribuição de energia elétrica, a temperatura ambiente e a precipitação de chuvas. O modelo linear de previsão de séries temporais utilizado foi um SARIMAX. A modelagem de inteligência computacional utilizada para a previsão da série temporal foi um sistema de Inferência Fuzzy. Na busca de um melhor desempenho, foram feitos testes de quais variáveis exógenas melhor influenciam no comportamento da energia distribuída em cada modelo. Segundo a avaliação dos testes, o sistema Fuzzy de previsão foi o que obteve o menor erro. Porém dentre os menores erros, os resultados dos testes também indicaram diferentes variáveis exógenas para cada modelo de previsão.

Proposta de um otimizador para rastreamento do ponto de máxima potência de um conjunto de painéis solares conectados em um sistema híbrido de energia.

Este trabalho apresenta o projeto e os algoritmos de controle, de um sistema de geração de energia híbrido. Este sistema é formado por conversores de potência conectados em Back-to-Back associados a um arranjo solar fotovoltaico, que por sua vez é conectado no lado CC dos conversores. Em relação ao sistema de geração fotovoltaico, a contribuição consiste no desenvolvimento de cinco algoritmos para determinar o ponto de máxima potência (MPP) do arranjo fotovoltaico. O primeiro algoritmo consiste em uma versão modificada do algoritmo de Perturbar e Observar (PeO); o segundo algoritmo proposto é baseado no método do gradiente (MG); e o terceiro é baseado na otimização do MG (MGO). Porém, são desenvolvidos algoritmos híbridos que combinam rede neural com o método PeO, e rede neural com o algoritmo MGO. O sistema foi desenvolvido e simulado utilizando o Matlab/Simulink, e os resultados de simulação são apresentados com objetivo da avaliar o comportamento do sistema e a resposta dos diferentes algoritmos. Esta resposta foi avaliada para condições transitórias e de regime permanente, considerando diferentes requisitos de consumo na carga, irradiância e temperatura.

Smart chemical sensor application of ZnO nanowires grown on CMOS compatible SOI microheater platform

Smart chemical sensor based on CMOS(complementary metal-oxide- semiconductor) compatible SOI(silicon on insulator) microheater platform was realized by facilitating ZnO nanowires growth on the small membrane at the relatively low temperature. Our SOI microheater platform can be operated at the very low power consumption with novel metal oxide sensing materials, like ZnO or SnO2 nanostructured materials which demand relatively high sensing temperature. In addition, our sol-gel growth method of ZnO nanowires on the SOI membrane was found to be very effective compared with ink-jetting or CVD growth techniques. These combined techniques give us the possibility of smart chemical sensor technology easily merged into the conventional semiconductor IC application. The physical properties of ZnO nanowire network grown by the solution-based method and its chemical sensing property also were reported in this paper.

Random lasing in a bistable smectic A liquid crystal

In this work, we examine the phenomenon of random lasing from the smectic A liquid crystal phase. We summarise our results to date on random lasing from the smectic A phase including the ability to control the output from the sample using applied electric fields. In addition, diffuse random lasing is demonstrated from the electrohydrodynamic instabilities of a smectic A liquid crystal phase that has been doped with a low concentration of ionic impurities. Using a siloxane-based liquid crystal doped with ionic impurities and a laser dye, nonresonant random laser emission is observed from the highly scattering texture of the smectic A phase which is stable in zero-field. With the application of a low frequency alternating current electric field, turbulence is induced due to motion of the ions. This is accompanied by a decrease in the emission linewidth and an increase in the intensity of the laser emission. The benefit in this case is that a field is not required to maintain the texture as the scattering and homeotropic states are both stable in zero field. This offers a lower power consumption alternative to the electric-field induced static scattering sample.