Three different topics associated with their respective applications are proposed in this thesis. The first application is the implementation of a fast tagged sorter. A novel and high-speed realization of the tagged sorting algorithm is presented. Meanwhile, the problems to detect whether the queue is empty or full is also resolved without increasing any hardware cost. The second topic is focused on the implementation of a fast dynamic 64-bit comparator with small transistor count. The entire 64-bit comparator is composed of equality comparators and zero/one detectors, which are proposed by C.-F. Wu. The problem to handle a large fan-in requirement is also resolved in our design. The third topic is to carry out a power demand monitor system for factories. Not only can it monitor the factory¡¦s power network with a graphical user interface, but also can turn off the unessential equipments automatically when the total power consumed by the factory is larger than what was expected.

In this study, we use a nonparametric technique, locally weighted robust least squares regression (LOESS), to forecast a 24 hour demand profile at the household level and compare it to existing aggregate demand models discussed in literature. Of these aggregate demand models, a quadratic autoregressive model was selected to be used as a basis for comparison with the LOESS forecasts. It was our goal to automate the forecasting process by using the goodness of fit metric, AICCI, for smoothing parameter selection. The statistical workflow was executed using SAS and data was provided by the Glasgow Electric Plant Board of Barren County, Kentucky. Results show that LOESS outperformed the autoregressive model in roughly 80% of all cases and than using LOESS alone or as part of an ensemble model is a feasible approach to automating future household demand profile for the purpose of generating different levels of power demand profile aggregation as needed by Glasgow Electronic Plant Board.

Thesis (Ph. D.)--Missouri University of Science and Technology, 2009. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed December 15, 2009) Includes bibliographical references (p. 72-80).

En el marco de un mercado de la electricidad con precios cada vez más altos y donde la participación de fuentes renovables de generación está jugando un papel cada vez más importante, esta tesis supone un enfoque innovador hacia la participación de recursos de demanda en mercados de operación, prestando una atención especial a segmentos industriales como el sector alimentario con un consumo energético intensivo. En primer lugar, esta tesis describe detalladamente la situación actual de los programas de respuesta de la demanda que existen en diferentes partes del mundo. Este estudio permite concluir que los consumidores no han sido tenidos en cuenta suficientemente en la fase de diseño de los programas existentes, lo que ha provocado la infrautilización de recursos de demanda que, actualmente, permanecen sin explorar. Por otro lado, los consumidores no son conscientes del valor que su flexibilidad podría tener para el sistema eléctrico en su conjunto, ignorando que puedan existir otros agentes dispuestos a pagarles a cambio de reducir sus cargas en períodos determinados. Como resultado, esta tesis desarrolla una nueva metodología para explorar y valorar nuevos mecanismos de respuesta de la demanda donde el punto de vista de consumidores, operadores de red y cualquier otro agente interesado pueda ser tenido en cuenta. Esta metodología, basada en la evaluación y análisis detallado de los procesos, proporciona a los consumidores las herramientas adecuadas para evaluar su capacidad para reaccionar al precio de la electricidad, lo que permitiría al regulador poner en valor el beneficio social de dicha flexibilidad si pudiera ser utilizada en mercados de operación, ayudándole a definir los programas necesarios para utilizar de forma adecuada el potencial identificado por los consumidores. La metodología desarrollada en esta tesis ha sido aplicada satisfactoriamente al sub-segmento de la industria cárnica, por lo que varias fábricas pertenecientes a este segmento han sido estudiadas en detalle. En concreto, la factibilidad de las acciones propuestas ha sido probada y validada satisfactoriamente en una fábrica dedicada a la producción de jamón curado en España, en la que se han evaluado diferentes estrategias de flexibilidad. Finalmente, se ha realizado una evaluación económica de la rentabilidad de la aplicación de las acciones de flexibilidad propuestas tanto para el consumidor como para el sistema eléctrico en su conjunto, donde se han considerado los precios reales de los mercados de operación en España, aun cuando los consumidores no puedan participar realmente en dichos mercados en la actualidad. / Alcázar Ortega, M. (2011). Evaluation and Assessment of New Demand Response Products based on the use of Flexibility in Industrial Processes: Application to the Food Industry [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10078 / Palancia

A Powerful Future explores the future electricity demand in Europe until 2050 for the industry, transport, and residential sector. This is done through a bottom-up model capturing the essential parameters for each sector combined with statistics on electricity and energy demand giving two scenarios on future power demand in Europe – High Electrification and Baseline. The electricity demand is built in Excel’s data modelling tool, at the request of Sweco. One aspect of this project also involves challenges when constructing this tool. The resolution will be yearly and economic aspects and feasibility of the electrification have not been investigated in this project. The focus of the project is to capture the most essential activities and technologies affecting the power demand in Europe to be included in the model, and less focus on analyzing each country. The annual results until 2050 for both scenarios show a significant increase in power demand in Europe due to the electrification of the industry and transport sector. The transport sector will reach approximately 550 TWh in Baseline and 600 TWh in High Electrification, while the industrial power demand will reach ~2 000/~2 700 TWh in the Baseline -/High Electrification scenario. These two sectors will account for the biggest increase in power demand while households will have a small increase in power demand. The total modeled annual electricity demand 2050 will be ~5 000/~5 900 TWh in the Baseline -/High Electrification scenario and will be approximately a doubling of the electricity demand 2021. / A Powerful Future utforskar den framtida efterfrågan av el i Europa fram till 2050 för industri, transport och hushållssektorn. Detta görs genom en bottom-up modell som infångar viktiga parametrar för varje sektor kombinerat med historiska data av energi- och elbehov för två olika scenarier för Europa –Baseline och Högelektrifiering. Elbehovet modelleras genom Excels datamodellerings-verktyg, som byggts på Swecos förfrågan. En aspekt i detta projekt involerar utmaningar när ett eget verktyg för detta ska konstrueras. Upplösningen är årlig och ekonomiska aspekter såväl som genomförbarhet har inte undersökts närmare i projektet. Resultat från projektet visar på en signifikant ökning i elbehov i Europa på grund av elektrifiering i industri- och transportsektorn. Transportsektorn kommer kräva circa 600 TWh el i Högelektrifieringsscenariet och 550 TWh i Baselinescenariet, emedan industrisektorns elbehov kommer att nå 2 000/2 700 TWh i Baseline-/Högelektrifieringsscenariet. Dessa två sektorer komma stå för den största ökningen i elbehov emedan hushållssektorn kommer stå för en liten ökning. Det totala elbehovet 2050 har modellerats till 5 000/5 900 TWh i Baseline-/Högelektrifieringsscenariet och är ungefär en fördubbling av elbehovet 2021.

La réduction des besoins dans les bâtiments à basse consommation d'énergie (BBC) nécessite un réexamen de l'approche de modélisation des systèmes énergétiques dans les outils de simulation. L'approche proposée repose sur une modélisation plus fine des phénomènes physiques incluant la régulation en boucle fermée du système énergétique couplé au bâtiment. A partir de l'identification des phénomènes propres au comportement énergétique des BBC, des recommandations, ou règles de modélisation, sont établies pour le développement des modèles de leurs systèmes énergétiques. Ces recommandations sont mises en application dans deux études. Tout d'abord, une simulation dynamique d'un bâtiment et de son système conduit à un dimensionnement plus adapté comparé aux méthodes classiques dans le cas de BBC avec des répercussions sur les appels de puissance et la consommation d'énergie. Ensuite, une analyse de sensibilité par la méthode de Morris sur une représentation générique du système énergétique a permis d'identifier les paramètres nécessitant d'être connus avec précision. La différence entre l'approche développée et la simulation horaire avec régulation idéale n'est que de quelques pourcents en besoins énergétiques pour un bâtiment existant mais elle passe à plus de 20% dans un bâtiment BBC. Un écart du même ordre de grandeur peut être identifié pour la détermination de la performance énergétique globale du système par une prise en compte plus détaillée des phénomènes de cyclage, de charge partielle ou de consommation des auxiliaires. / The decrease of heat demands in low energy buildings requires to examine again modeling approaches in building energy simulation tools. The developed approach is based on a more accurate modeling of physical phenomena including the closed loop control between the HVAC system and the building. From the identification of the phenomena that specifically impact the energy behavior of the low energy buildings, some recommendation, or modeling rule, are established for the development of their HVAC systems. Those recommendations are applied in two case studies. Firstly, a dynamic simulation of a building and its system offers a better evaluation of the design power for a low energy building, affecting power demands and energy consumption. Then, a sensitivity analysis from Morris method on a generic representation of the HVAC system identifies the parameters to be accurately known. The difference between the developed approach and an hourly simulation with an ideal control is low for the evaluation of the heat load in an existing building but it is more than 20% in a low energy buildings. A difference of the same order of magnitude can be identified in the determination of the overall energy performance of the system by a more detailed consideration of the phenomena of cycling, the part load or the consumption of auxiliaries.

With regard to autonomous driving the demands on comfort are increasing. This makes it attractive to use active suspension systems. The system developed at TU Darmstadt is able to increase driving comfort up to 28 % while maintaining driving safety compared to a passive suspension system. This paper investigates the influence of available energy and power of the active system. The investigation is based on a simulation of a quarter car model and an uneven country road. This paper shows that the more energy the active system has at its disposition, the greater is the range between a comfortable and a sporty chassis. Furthermore the driving comfort can be increased by 28 % with constant driving safety. The average power required for this is 15 W and the maximum power is 300 W.

The architectures of large-scale Internet servers are becoming more complex each year in order to store and process a large amount of Internet data (Big Data) as efficiently as possible. One of the consequences of this continually growing complexity is that individual servers consume a significant amount of data even when they are idle. In this paper we experimentally investigate the scope and usefulness of existing and proposed dynamic power management strategies to manage power at core, socket, and server levels. Our experiment involves four dynamic voltage and frequency scaling policies, three different workloads having different resource consumption statistics, and the activation and deactivation of different sockets (packets) of a multicore, multi-socket server. Moreover, we establish a quantitative relationships between the workload (w) and the estimated power consumption (p) under different power management strategies to make a quantitative comparison of the different strategies and server configurations.

Data processing on a continuously growing amount of information and the increasing power restrictions have become an ubiquitous challenge in our world today. Besides parallel computing, a promising approach to improve the energy efficiency of current systems is to integrate specialized hardware. This paper presents a Tensilica RISC processor extended with an instruction set to accelerate basic database operators frequently used in modern database systems. The core was taped out in a 28 nm SLP CMOS technology and allows energy-efficient query processing as well as query optimization by applying selectivity estimation techniques. Our chip measurements show an 1000x energy improvement on selected database operators compared to state-of-the-art systems.

Uppsala Municipality is planning to build the southeast city district (SÖS), aiming to achieve climate neutrality by 2030 and climate positivity by 2050. In this thesis, the integration of electric vehicles (EVs) and charging infrastructure was investigated. It also examined the power demand, and the potential of photovoltaic (PV) production in combination with a battery storage system in SÖS, and its ability to reduce power peaks. The study was delimited to only incorporating charging demand in mobility houses, not from the private parking spots, as well as excluding alternative fossil-free vehicle options. Utilizing a stochastic model and data from Copenhagen and Stockholm, using trends for car pools and EV ratio, two scenarios were designed to forecast the spread of EVs and their impact on the power grid in SÖS by 2050. Since SÖS consists of both residential housing and workplaces, three different simulations were created to take their differences in mobility pattern into account. The two scenarios generated a different number of EVs, which resulted in a varied amount of charging points. Furthermore, the difference in EVs and mobility patterns showed different values of power demands and power peaks. PV panels combined with a battery storage system were able to both reduce the daily power demand, as well as the power peaks. For the sensitivity analysis, different sizes of the battery storage were examined. Finally, this report presents guidance for how to manage the challenges with an increased power demand from the more extensive use of EVs.