1,543,959 research outputs found

    Toward a Unified Performance and Power Consumption NAND Flash Memory Model of Embedded and Solid State Secondary Storage Systems

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    This paper presents a set of models dedicated to describe a flash storage subsystem structure, functions, performance and power consumption behaviors. These models cover a large range of today's NAND flash memory applications. They are designed to be implemented in simulation tools allowing to estimate and compare performance and power consumption of I/O requests on flash memory based storage systems. Such tools can also help in designing and validating new flash storage systems and management mechanisms. This work is integrated in a global project aiming to build a framework simulating complex flash storage hierarchies for performance and power consumption analysis. This tool will be highly configurable and modular with various levels of usage complexity according to the required aim: from a software user point of view for simulating storage systems, to a developer point of view for designing, testing and validating new flash storage management systems

    Lightweigth Adaptive fault-tolerant data storage system (AFTSYS)

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    Research group ARCOS of Universidad Carlos III de Madrid (Spain) have been working on flexible and adaptive data storage systems for several years. The storage systems developed are featured by software governance, making them portable across different hardware storage resources, and their dynamic adaptativy to the different circumstances of computer systems following the autonomic system paradigm. They also allow getting high performance storage by using data distribution or striping across multiple devices. One of the group’s technologies y the AFTSYS system. A fault-tolerant storage system for persistent distributed objects, user configurable and adaptive to system behaviour

    A review of solar collectors and thermal energy storage in solar thermal applications

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    Thermal applications are drawing increasing attention in the solar energy research field, due to their high performance in energy storage density and energy conversion efficiency. In these applications, solar collectors and thermal energy storage systems are the two core components. This paper focuses on the latest developments and advances in solar thermal applications, providing a review of solar collectors and thermal energy storage systems. Various types of solar collectors are reviewed and discussed, including both non-concentrating collectors (low temperature applications) and concentrating collectors (high temperature applications). These are studied in terms of optical optimisation, heat loss reduction, heat recuperation enhancement and different sun-tracking mechanisms. Various types of thermal energy storage systems are also reviewed and discussed, including sensible heat storage, latent heat storage, chemical storage and cascaded storage. They are studied in terms of design criteria, material selection and different heat transfer enhancement technologies. Last but not least, existing and future solar power stations are overviewed.Peer reviewe

    The SERI solar energy storage program

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    In support of the DOE thermal and chemical energy storage program, the solar energy storage program (SERI) provides research on advanced technologies, systems analyses, and assessments of thermal energy storage for solar applications in support of the Thermal and Chemical Energy Storage Program of the DOE Division of Energy Storage Systems. Currently, research is in progress on direct contact latent heat storage and thermochemical energy storage and transport. Systems analyses are being performed of thermal energy storage for solar thermal applications, and surveys and assessments are being prepared of thermal energy storage in solar applications. A ranking methodology for comparing thermal storage systems (performance and cost) is presented. Research in latent heat storage and thermochemical storage and transport is reported

    Hybrid and Intelligent Energy Storage Systems in Standalone Photovoltaic Applications.

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    Remote systems such as communication relays or irrigation control installations cannot usually be powered by the electrical grid. One of the alternatives is to power these systems through solar panels, in what is known as standalone photovoltaic applications.Most of these systems need a continuous operation, but a standalone photovoltaic installation cannot be powered during the night. For this reason, they use batteries to store excess energy during the day. These storage systems have been traditionally based on Valve Regulated Lead Acid (VRLA) batteries, but some effects can alter their performance in terms of reliability, operation cost and maintenance. One of the key issues that alter the energy behavior of the photovoltaic off-grid systems is the Partial State of Charge (PSoC) effect: Batteries cannot be completely charged as manufacturers indicate due to the day-night cycle. This gets the battery into an intermediate state of charge that effectively reduces its capacity, even halving it in some cases. To mitigate the impact of these effects on the installation, batteries tend to be oversized with some security margins. These oversizing factors can be incredibly high and have a huge impact on the deployment and maintenance cost of the facility.The first part of this thesis highlights some of these key concepts, analyzing which of them are critical in specific design cases, modeling them into a simulation tool, and as an outcome, establishing optimal sizing regions for the installations. After the analysis, different ways of improving the performance of the installations are proposed. One idea to mitigate PSoC is to combine different storage technologies in a Hybrid Energy Storage Systems (HESS). HESSs have traditionally combined high energy density elements as batteries with high power density elements as ultracapacitors. An iteration of this idea is carried out throughout this thesis, where different types of batteries are combined. Each of them is best fitted to different power patterns in the application, such as daily cycles or emergency periods. It is possible to further increase the performance by using intelligent algorithms to improve the functionalities of the Battery Management Systems embedded in these applications. To this end, failure prediction and health estimation algorithms are proposed as contributions of this work. These new algorithms endow the HESS with tools to predict possible energy disruption events and to anticipate aging, and thus, act accordingly.<br /
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