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Organic photovoltaics (OPV) represent the newest generation of technologies in solar power generation, offering the benefits of flexibility, low weight and low cost enabling the development of new consumer nomadic applications and the long term perspective of easy deployment in Building Integrated Photo Voltaics (BIPV) and energy production farms. This is a key opportunity for the EU to further establish its innovation base in alternative energies. The current challenges reside in the combination to increase efficiencies to 8-10Prozent (module level), increase expected lifetime up to 20 years and decrease production costs to 0.7 Eur/Wp, while taking into account the environmental impact and footprint. The key project objectives are to achieve: - Printed OPV with high efficiency architectures such as tandem cells and dedicated light management structures - High performance photo active and passive (barrier) materials including process controlled morphology - Solutions for cost effective flexible substrates, diffusion barriers and conductors - Deep understanding of the device physics, elucidation of degradation mechanisms and estimate environmental impact of the main materials and processes. The project consortium combines industrial, institutional and academic support to make a significant impact at European and International level, especially on materials and processes while demonstrating their market-relevant implementations. The industrial project partners are well assembled along the supply chain of future OPV-based products, which is an important prerequisite for the creation of significant socio-economic impact of this proposal.
Data centres are involved play two different and complementary roles in Smart Cities' energy policies with two roles: as ICT infrastructures supporting Smart City resource optimization systems - and more in general, delivering for ICT services to the citizens - and as large energy consumers. Therefore there are huge expectations on data centres being able to run at the highest levels of renewable energy sources: this is the great challenge of DC4Cities project. DC4Cities addresses these requirements optimizing data centre operations as well as software running in the data centre for minimal energy consumption and adaptivity to external energy constrains, targeting the 80% usage of renewable energy sources. The goal of DC4Cities is to let make existing and new data centres become energy adaptive, without requiring any logistics modification to the logistics, and without impacting the quality of the services provided to their users. Finally new energy metrics, benchmarks, and measurement processes will be developed and proposed for the definition of new related standards. DC4Cities will promote the data centres role as an 'eco-friendly' key player in the Smart Cities energy policies, and will foster the integration of a network of local renewable energy providers (also interconnected with local Smart Grids and microgrids) to support the pursued increase of renewable energy share.
COBRA is a coordination action to help organize the international CHEM-IT community towards the next major science and technology revolution, involving the integration of information processing with production during deployment. The industrial revolution mechanized production with factories, and the information revolution mechanized information processing with computers. The next large-scale technological revolution most likely involves their integration and its decentralization, as found so far only in living systems and it is now clear that significant scientific and technical progress towards this integration is imminent. The EC-sponsored CHEM-IT projects are spearheading the development and exploration of the first simple systems integrating production and information processing. This is done at the nano-bio-info interface, involving cellular engineering, protocells, artificial neurons and programmable information chemistry. At the centre of this work is a desire to create ICT-based systems with living and intelligent desirable properties that current technologies lack (such as robustness, autonomy, self-repair, adaptation, learning and local intelligence, as well as self-replication and evolution). The potential long-term impact of this emerging enabling technology will be considerable, as even minor progress on making technology more life-like and intelligent can improve processes in all sectors of society. CHEM-IT addresses issues of sustainability in production and deployment, and the information explosion of ubiquitous nanoscale systems. The proposed project on the coordination of biological and chemical IT research activities (COBRA) seeks to engage the European research community to construct the first roadmap for how best to develop ICT-based integrated information processing and production technology.
Scientists develop computer models of real, complex systems to increase understanding of their behaviour and make predictions. A prime example is the Earth's climate. Complex climate models are used to compute the climate change in response to expected changes in the composition of the atmosphere due to man-made emissions. Years of research have improved the ability to simulate the climate of the recent past but these models are still far from perfect. The model projections of the globally averaged temperature increase by the end of this century differ by as much as a factor of two, and differ completely in regard to projections for specific regions of the globe. Current practice commonly averages the predictions of the separate models. Our proposed approach is instead to form a consensus by combining the models into one super model. The super model has learned from past observations how to optimally exchange information among individual models at every moment in time. Results in nonlinear dynamics suggest that the models can be made to synchronize with each other even if only a small amount of information is exchanged, forming a consensus that best represents reality. This innovative approach to reduce uncertainty might be compared to a group of scientists resolving their differences through dialogue, rather than simply voting or averaging their opinions. Experts from non-linear dynamics, machine-learning and climate science are brought together within SUMO to produce a climate change simulation with a super model combining state-of-the-art climate models. The super-modelling concept has the potential to provide improved estimates of global and regional climate change, so as to motivate and inform policy decisions. The approach is applicable in other situations where a small number of alternative models exist of the same real-world complex system, as in economy, ecology or biology.
Meeresdaten werden sowohl in der wissenschaftlichen als auch in der angewandten Forschung benötigt, zunehmend jedoch auch in der Wirtschaft. Geologische und geophysikalische Daten stellen eine wichtige Kategorie solcher Daten dar und potentielle Nutzer verlangen den einfachen Zugang zu marinen geologischen und geophysikalischen Daten, Datenprodukten und Dienstleistungen. In Europa wird basierend auf Technologien und Standards des 'SeaDataNet'- Projektes mit dem GeoSeas-Projekt eine e-Infrastruktur mit 26 marin-geologischen und geophysikalischen Datenzentren in Europa aufgebaut. Die Daten der Sedimentbeschaffenheit in der Nordsee wurden mit dem Common Data Index beschrieben und die Daten selbst für den Downloadmanager in standardisierter Form bereitgestellt. Die Daten sind im Format des Ocean Data View (ODV) aus der Datenbank des DOD ausgegeben und weiterverarbeitet worden. Bisher wurden 1563 dieser Datensätze bereitgestellt, mehr als 8000 seismische Ereignisse (Erdbeben) wurden aufbereitet und werden derzeit in das ODV-Format transferiert. Es ist geplant, weitere geologische Daten wie Cone Penetration Test-Daten ebenso wie auch zur Sedimentzusammensetzung oder Dichte vorzubereiten. Für einige Datentypen sind geeignete Standards zu vereinbaren.
Goals: Many of today's technical blessings, e.g. weather forecast, fuel efficient car-shapes, medical tomography analysis or even a simple Google query depend on massive computer programs that are executed on super-computing centers with thousands of computers, which consume a lot of electrical energy. With increasing super-computing demand severe economic and ecological problems arise. Already 15% of the world-wide electrical energy is used to power all the computers in use today, and this number is quickly increasing. There are alternative kinds of computing devices such as smart-phone processors, 3D graphic chips and reconfigurable FPGA hardware (as used in DSL modems and network switches), which can provide much higher energy efficiency than traditional processors. Today, a typical super-computing program consists of a huge number of small jobs. Some of them can be run on these alternative architectures, reducing the demand and therefore the required number of traditional high-energy, high performance processors. Motivation: The FiPS project thus proposes to build a new heterogeneous super-computer class. It combines traditional high performance processors for complex tasks with many of the efficient alternative processors for simple tasks. As the total number of processors increases, these new super-computers will be slightly faster, but will at the same time substantially reduce the energy demand. FiPS will not only have an ecological impact by reducing energy demand (and thus carbon dioxide emission), but also an economic impact by cutting one of the major costs of running a super-computing center, its energy costs. Supercomputing will become cheaper and thus affordable for many other applications. Promotion: This project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 609757. Technology: The drawback of building super-computers from a heterogeneous network of processors rather than a regular grid of identical processors is that heterogeneous systems are much harder to program, as the individual properties of many different components have to be considered. For instance, different processors require different programming languages, and it has to be decided, which processor type will finally run a computation job, either to get the result as fast as possible or with the lowest energy costs. And finally, all processors working on different parts of the same problem have to synchronize on their intermediate results. This is up to now only possible in a regular grid of homogeneous processors. To solve these issues, FiPS will setup a programming methodology, in which just a single programming language is used to write the super-computing program. The final software is then analyzed and splitted into chunks by the FiPS methodology. (abridged text)
In recent years, electric mobility has been promoted as the clean and cost-efficient alternative to combustion engines. Although there are already solutions on the market, mass take-up has not yet taken place. There are different challenges that hinder this process from an end user point of view such as costs of the vehicle, driving range, or infrastructure support. Several of these challenges are directly connected to the battery, the central element of the full electric vehicle (FEV). The costs of the battery sum up to 40Prozent of the total costs of a FEV, and the driving range of a FEV is strongly reduced in comparison to the combustion engine. The aim of INCOBAT is to provide innovative and cost efficient battery management systems for next generation HV-batteries. To that end, INCOBAT will propose a platform concept in order to achieve cost reduction, reduced complexity, increased reliability as well as flexibility and higher energy efficiency. The main outcomes of the project will be: - Very tight control of the cell function leading to an increase of the driving range of the FEV by 30Prozent for current chemistry and by a factor of 10 and more by enabling the use of new cell chemistries such as LiS or even Li-air - Radical cost reduction of battery management system - factor of 10 (at least) with respect to current solutions - Development of modular concepts for system architecture and partitioning, safety, security, reliability as well as verification and validation, thus enabling efficient integration into different vehicle platforms. INCOBAT is in the position to provide a 100Prozent European value chain for the development of next generation HV battery management systems.
The interest in the carbon footprint of Data Centres (DCs) has become more urgent with the rapid increase in Cloud computing, High-Powered Computing, and the vast growth in Internet use, and of DCs as key enablers of this paradigm. However, whereas energy efficiency is necessary to reduce ecological impact of DCs, it is not enough. In addition, the carbon emissions of DCs are greatly influenced by the energy sources used, the operation of the DC, the connection to energy infrastructures in our cities and integration of Renewable Energy Sources (RES). Planners, managers, investors, owners and designers of DCs lack the necessary tools capable of evaluating the environmental performance and the share of RES in the emerging concept of Net Zero Energy DCs. - The main objective of the RenewIT is to develop a simulation tool to evaluate the energy performance of different technical solution integrating RES in several European climate regions. The public RenewIT tool will be implemented in a user-friendly web interface helping actors from both the energy and IT sectors to reduce the carbon footprint of planned DCs in the horizon of 2030. The tool is based on selected meta-models extracted from advanced dynamic simulation models of challenging energy concepts for renewable energy supply of DCs. - A set of challenging energy concepts will be developed in the framework of the project under an holistic approach integrating the following technical solutions: management of the IT load following 'green' objectives, low-energy air-conditioning systems, solar cooling, interaction with district heating and cooling networks, re-use of heat, optimal use of heat and cold storage, and integration in smart grids. The technical systems emerging from the energy concepts are modelled in dynamic simulation tools creating a family of new components which will be integrated in the Green DC library of components as an exploitable output of the project. Harmonised metrics able to rank the energy performance of DCs will be developed and implemented in the software tools as a result of co-ordinated work with relevant standardisation organisations, industry bodies, and other European projects. In addition, these harmonised metrics will be part of a high-quality monitoring system to monitor DCs integrating renewables. - A validation process will be developed, in close collaboration with four DCs in Southern Europe and four DCs in Northern Europe, which will exchange continuous feedback with the technical developers throughout the project. The validation process will be based on built case studies for live DCs as the means of testing the robustness and the end-user applicability both of the developed technical energy concepts and of the simulation software tools. - The project outputs will be widely disseminated throughout the project lifetime, through scientific and industry publications, web site and social media, and attendance at relevant conferences and industry forums.
The BaaS system aims to optimize energy performance in the application domain of 'non-residential buildings, in operational stage. In the building operational life-cycle three significant tasks have to be continuously performed: collect information and assessment of the buildings current state (identifying possible faults and inefficiencies if they exist); prediction of the effect that various decisions will have to Key Performance Indicators (KPIs); and optimized operation of systems to achieve high operational performance. A generic ICT-enabled system will be developed to provide integrated services that guarantee harmonious and parsimonious use of available resources. - The BaaS system comprises four components: 1. A data management component to collect, organize, store and aggregate data from various in- and out-of-building sources. An (IFC-based) BIM will act as a central repository for all static building data, and a data warehouse will be used for dynamic data. 2. A service middleware platform to abstract the building physical devices, support high level services on the cloud and facilitate secure two-way communication between the physical and ICT layers (building) with high level services (cloud). 3. Energy models for performance estimation and for control services, looking for a trade-off between prediction accuracy (performance estimation) and computational complexity (fast-model for control design). 4. Analytics Services not for assessment and prediction services: simulation models, acting as surrogates of the real building, incorporating sensor dynamic data, will be used to assess performance and comprehensively estimate the values of relevant KPIs as well as help perform sensitivity analyses; not for building automatic and control (BAC) services, automatically will generate holistic nearly-optimal control strategies with the goal of achieving operational efficiencies as measured through relevant KPIs and will be imbued with adaptive and re-configurability properties to respond to faults and atypical scenarios. - Upon verification of component interoperability, and development of a measurement and verification plan, the BaaS system will be demonstrated in real buildings and will be validated as an Energy Conservation Measure with Energy-Services Companies as the end-user. - End-user acceptance will be accomplished by analyzing the replication potential in tandem with the results of a sensibility study. - Keywords-Energy efficiency in buildings, Data Warehouse, Data Interoperability, Middleware Platform, Energy Modelling and Simulation, Automation and Control Systems, Anomaly Identification, Energy Savings M&V Methodology.
The EXA2GREEN project aims at developing a radically new energy aware computing paradigm and programming methodology for exascale computing. The key aspect of the proposed approach is that the issue of energy consumption and the resulting trade-off with the performance and the accuracy of the overall simulation process will be taken into account in all simulation levels: from the kernel, numerical/combinatorial building blocks to the application level by means of the considered mathematical models. The proposed approach of Energy-Aware Numerics goes beyond the standard hardware level or operating software stack usually considered for energy issues and puts the application in the centre of the scene for all aspects related to energy efficiency. The EXA2GREEN project takes up this multidisciplinary challenge by bringing together HPC experts, computer scientists, mathematicians, physicists and engineers. The project team is part of an emerging, multidisciplinary European research community and covers all essential fields of expertise, which allow opening absolutely new perspectives in the area of energy-aware numerics in the exascale era. The overall goal of this project is to develop unconventional ideas in order to cope with the issue of power consumption. Reducing the power requirement by a factor of at least 100 is the challenge which needs to be addressed in order to be able to use this technology in a meaningful way. This is one of the reason why making the transition to exascale computing requests radical transformation in the current perception of numerical simulation in high performance computing. The viability of the proposed approach will be investigated considering a proof of concept where the energy footprint of a large and operational meteorological model for atmospheric and aerosol simulation (COSMO-ART) will be analysed.
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