Other language confidence: 0.8827442542427024
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.
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.
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.
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.
The objective of FINESCE was to: Transform Energy infrastructures towards Smart Energy systems by trialling network enabled applications using common functionality provided by Fi-WARE, developing novel service layer enhancements encapsulated in the FINESCE-API, and by enabling the development of innovation opportunities for ICT and Utility actors as well as in the community providing public services. FINESCE (Future INtErnet Smart Utility ServiCEs) was the smart energy use case project of the 2nd phase of Future Internet Public Private Partnership (FI-PPP) program funded by the European Union within FP7. From 2013 until 2015, FINESCE contributed to the development of an open IT-infrastructure to be used to develop and offer new app-based solutions in all fields of the Future Internet. The project organised and ran a series of field trials at trial sites in 7 European countries. Change is the name of the game in energy! The shift to sustainability is visible everywhere. It is now a European priority to combine solutions which utilise energy generation from renewable energy sources and optimize energy usage efficiency into a Smart Energy System based on the introduction of Future Internet technologies. At the same time, business innovation needs to be encouraged to ensure that job creating SME's can thrive in the new energy eco-system. FINESCE organised and ran user trials in 7 European countries, building on investments of billions of Euro, addressing efficient energy usage in residential and industrial buildings, developing a new prosumer energy marketplace, building a cross-border private virtual power plant, and using electric vehicles as an element of demand response systems, enabling energy providers to move from reactive to pro-active energy network management by providing them with Future Internet ICT, enabling them to better balance volatile solar and wind energy generation with demand for energy. The FINESCE trials proved the practical applicability of Future Internet technologies and the FI-WARE Generic Enablers to the challenges of the energy sector. FINESCE developed an active community of innovative SME's, preparing them for the exploitation of the emerging business opportunities in energy, creating jobs, social impact and economic growth. FINESCE built on and extended the results of the FI-PPP FINSENY project to realise sustainable real time smart energy services. The consortium included globally leading energy and ICT operators, manufacturers and service providers and outstanding research organisations and SME's, from 12 countries, contributing directly to tightly focused trials and business innovation. It had the scale and scope to ensure that the FINESCE results drive the FI-WARE and Future Internet success and long-term exploitation internationally.
With the advent of Smart Grids the development and adoption of standards ensuring interoperability and security become of utmost importance in the field of electricity networks. The STARGRID project has been initiated by the European Commission in 2012 to provide a clear overview of the current Smart Grid standardisation activities, to lay down requirements and evaluation criteria for Smart Grid standards, and to work out recommendations on the future strategy of the Commission on this topic. A particular focus of the project is on industry requirements. The STARGRID project aims to obtain a comprehensive picture of Smart Grid standardisation procedures and to critically assess the large and complex standardisation landscape on Smart Grids at international level, including the industry new developments and initiatives in this field. - The standards analysis to be accomplished during the project will consider the available results of the Smart Grid Coordination Group (SGCG) and other groups. Despite this, the STARGRID Consortium will provide a view independent from interest of those stakeholders (utilities, large manufacturers,...) participating in the standardisation committees or coordination groups. STARGRID will incorporate the view and opinion of the industry about the smart grid standards, extending the scope beyond the EU 'Smart Grid Mandate' M490. - Many experts are convinced that the main obstacle for turning the Smart Grid into reality will not be the lack of applicable and mature standards but the adoption and implementation across the broad range of technologies concerned. With many projects already underway and a wide range of technical and business scenarios discussed, there seems to be a lack of standards awareness. STARGRID interaction with industry aims to mitigate this barrier for smart grids effective deployment. - The described concept of the STARGRID proposal is implemented through the following specific objectives of the project: - Compile, organise and distil both existing standardisation documents and industry initiatives information on smart grids at international level, to establish the State of the Art in this field. - Analysis of the gathered material according to a defined methodology and criteria. - Incorporation to the assessment process of the view of the industry of both power and ICT sectors by means of interviews, workshops, fair visits, etc. - Dissemination of the analysis results, conclusions and recommendations to the industry, standardisation organisation and to the European Commission.
NRG4Cast is developing real-time management, analytics and forecasting services for energy distribution networks in urban/rural communities. We are analysing information regarding network topology and devices, energy demand and consumption, environmental data and energy prices data NRG4Cast is developing real-time management, analytics and forecasting services for energy distribution networks in urban/rural communities. We are analysing information regarding network topology and devices, energy demand and consumption, environmental data and energy prices data. The services that will be integrated in a software module pipeline providing prediction and the decision support system based on network monitoring, anomaly detection, route cause analysis, trend detection, planning and optimisation. These services will be using advanced knowledge technologies in particular machine learning, data and text mining, stream mining, link analysis, information extraction, knowledge formalisation and reasoning. The platform will be tested in the two orthogonal case studies energy efficiency in municipalities and energy efficiency in city districts. The two case studies will be complemented with the additional energy networks operated by project partners; electric vehicles network, public lighting system and energy positive buildings. The proposal concentrates on electric power networks through the development of a generic framework that will be able to control, manage, analyse and predict behaviour in an extensible manner on other energy networks like gas distribution, heat water distribution and alternative energy distribution networks. For these reasons a generic toolkit with programmable data adapters will also be developed. Proposal gathers highly competent RTD organisations, developers, energy operators and case studies from four European countries. The project is led by JSI, has a consortium of 8 partners from 4 different countries and will run for 36 months.
| Organisation | Count |
|---|---|
| Bund | 35 |
| Europa | 35 |
| Wissenschaft | 12 |
| Type | Count |
|---|---|
| Förderprogramm | 35 |
| License | Count |
|---|---|
| Offen | 35 |
| Language | Count |
|---|---|
| Deutsch | 2 |
| Englisch | 35 |
| Resource type | Count |
|---|---|
| Keine | 17 |
| Webseite | 18 |
| Topic | Count |
|---|---|
| Boden | 32 |
| Lebewesen und Lebensräume | 31 |
| Luft | 26 |
| Mensch und Umwelt | 35 |
| Wasser | 18 |
| Weitere | 35 |