ABB AS
ABB AS
9 Projects, page 1 of 2
Open Access Mandate for Publications and Research data assignment_turned_in Project2019 - 2021Partners:Umeå University, FRANCE DIGITALE, PG WCONSULTING SARL, INRIA, ABB AS +79 partnersUmeå University,FRANCE DIGITALE,PG WCONSULTING SARL,INRIA,ABB AS,VUB,CERTH,QWANT,THOMSON LICENSING,IST ID,CARTIF,GRASSROOTS ARTS AND RESEARCH UG (HAFTUNGSBESCHRANKT),ALLIANZ SE,THALES,UNILEVER U.K. CENTRAL RESOURCES LIMITED,Institut de recherche Idiap,UNIVERSITE PARIS I PANTHEON-SORBONNE,THALES ALENIA SPACE FRANCE,INTERDIGITAL R&D FRANCE,EIT DIGITAL,FOUNDATION FOR RESEARCH AND TECHNOLOGYHELLAS,TUKE,HUB FRANCE IA,BLUMORPHO,UPM,CEA,CNRS,GoodAI Research,UPC,UCC,TELENOR ASA,UNIBO,IMT,SAP AG,Wavestone,Know Center,ONERA,UGA,UCG,Ca Foscari University of Venice,CNR,BUTE,RADIO- JATELEVISIOTEKNIIKAN TUTKIMUS RTT,HTW Berlin,UNISI,Sorbonne University,NTNU,National Centre of Scientific Research Demokritos,INTERNATIONAL DATA SPACES ASSOCIATION IDSA,Simula Research Laboratory,TILDE,Cineca,JSI,Thalgo (France),Aristotle University of Thessaloniki,TUW,DLR,BRGM,DFKI,WOMEN IN AI,BLUE-SIGHT CONSEIL,NEHS DEVELOPPEMENT,UoA,ELTE,KIT,CSIC,ATOS SPAIN SA,FBK,FBR,BSC,LOUPE 16 LTD,SMILE,TUM,SMARTRURAL SLL,University of Leeds,TU Berlin,Siemens (Germany),Örebro University,TWENTY COMMUNICATIONS,Sapienza University of Rome,FHG,Orange (France),University of Coimbra,EOSFunder: European Commission Project Code: 825619Overall Budget: 20,667,700 EURFunder Contribution: 20,000,000 EURArtificial Intelligence is a disruptive technology of our times with expected impacts rivalling those of electricity or printing. Resources for innovation are currently dominated by giant tech companies in North America and China. To ensure European independence and leadership, we must invest wisely by bundling, connecting and opening our AI resources. AI4EU will efficiently build a comprehensive European AI-on-demand platform to lower barriers to innovation, to boost technology transfer and catalyse the growth of start-ups and SMEs in all sectors through Open calls and other actions. The platform will act as a broker, developer and one-stop shop providing and showcasing services, expertise, algorithms, software frameworks, development tools, components, modules, data, computing resources, prototyping functions and access to funding. Training will enable different user communities (engineers, civic leaders, etc.) to obtain skills and certifications. The AI4EU Platform will establish a world reference, built upon and interoperable with existing AI and data components (e.g. the Acumos open-source framework, QWT search engine..) and platforms. It will mobilize the whole European AI ecosystem and already unites 80 partners in 21 countries including researchers, innovators and related talents. Eight industry-driven AI pilots will demonstrate the value of the platform as an innovation tool. In order to enhance the platform, research on five key interconnected AI scientific areas will be carried out using platform technologies and results will be implemented. The pilots and research will showcase how AI4EU can stimulate scientific discovery and technological innovation. The AI4EU Ethical Observatory will be established to ensure the respect of human centred AI values and European regulations. Sustainability will be ensured via the creation of the AI4EU Foundation. The results will feed a new and comprehensive Strategic Research Innovation Agenda for Europe.
more_vert Open Access Mandate for Publications assignment_turned_in Project2016 - 2019Partners:ABB AS, Jagiellonian University, Imperial, Cranfield University, TU Dortmund University +6 partnersABB AS,Jagiellonian University,Imperial,Cranfield University,TU Dortmund University,University of Valladolid,ABB SPZOO,NTNU,BASF SE,AST,ABB AG MannheimFunder: European Commission Project Code: 675215Overall Budget: 3,629,760 EURFunder Contribution: 3,629,760 EURThe typical lifetime of an industrial process plant is between 30 and 50 years. Technologies to enhance the operation and optimization of process plants can both guide the development of new state-of-the-art process plants and, perhaps more pertinently, can ensure that the large installed base of existing plants operates efficiently. The PRONTO Consortium partners are strongly convinced that for Europe to stay competitive, the overriding challenge is the efficient and sustainable operation of assets already installed and running at the present time. Production involves flows of material and energy over an extended area through the distributed and interconnected equipment of the process network. Process plants also generate complex information from disparate sources in the form of measurements from the process, mechanical and electrical sub-systems, and elsewhere. Efficient and sustainable operation of assets over a timescale of 30-50 years therefore requires sophisticated approaches for managing information and managing resources to ensure optimal operation. The research topics of PRONTO are (i) data analytics for assessment of the condition and performance of networks of equipment used for production in the process industries, (ii) optimization of use of resources in process networks taking account of real-time information about the condition and performance of the process equipment, and (iii) new concepts for process operation identified as having high potential for impact by industrial partners. The consortium partners include leading universities and well-known companies with high reputations for innovation. The consortium offers the early stage researchers training under the European Industrial Doctorate scheme by involving the non-academic sector extensively in joint supervision of the doctoral training with a strong emphasis on industrially-relevant PhD projects leading to practical demonstrations.
more_vert assignment_turned_in Project2010 - 2014Partners:SNETT, ABB AS, Graz University of Technology, AALTO, FGRID +5 partnersSNETT,ABB AS,Graz University of Technology,AALTO,FGRID,GENERAL ELECTRIC DEUTSCHLAND HOLDING GMBH,NGRID,Imperial,ABB (Switzerland),ABB SPZOOFunder: European Commission Project Code: 251304more_vert assignment_turned_in Project2014 - 2017Partners:ZIV, KTH, INCODE, TNO, Liander (Netherlands) +5 partnersZIV,KTH,INCODE,TNO,Liander (Netherlands),ABB AS,EDP DISTR,ENCS,SICS,FFCULFunder: European Commission Project Code: 607109more_vert Open Access Mandate for Publications assignment_turned_in Project2018 - 2022Partners:Uppsala University, Luleå University of Technology, Statkraft (Norway), NTNU, SINTEF AS +11 partnersUppsala University,Luleå University of Technology,Statkraft (Norway),NTNU,SINTEF AS,Saints Cyril and Methodius University of Skopje,EDR & MEDESO AS,Chalmers University of Technology,ABB AS,RAINPOWER NORGE AS,Multiconsult (Norway),Lyse Produksjon AS,University of Strathclyde,NINA,VATTENFALL AB,RWTHFunder: European Commission Project Code: 764011Overall Budget: 5,716,990 EURFunder Contribution: 5,426,690 EURHydroFlex aims to increase the value of hydro power through increased Flexibility. The commitment to cut greenhouse gas emissions under the United Nations Framework Convention on Climate Change has been an important contributor to the increasing share of renewables in the European energy system. Variable renewable energy sources such as wind and solar, as well as increased end-user flexibility and a market-oriented operation of power plants, results in larger fluctuations in the power system. Hydro power, due to its quick response and storage capability represents an important asset for grid balancing. HydroFlex aims to make hydro power available in a time as short as possible by performing well-focused research and innovation actions on the key bottlenecks of hydro power plants that restricts their flexibility. The project will start off by identifying the operating conditions of hydro power plants in the future energy system. Research will be focused on the flexibility of Francis turbines, the most common turbine type in Europe, and the configuration of synchronous generators and frequency converters that allow for variable speed operation. Variable speed operation increases the operating range of the turbines, reduces the fatigue loads, and allow for higher ramping rates and start-stop-cycles reaching up to 30 times per day. HydroFlex also addresses methods to mitigate the negative effects on downstream water courses that may result from higher flexibility of hydro power plants, by developing and testing a technology for active underground storage of water. To promote the research results to the hydro power industry, the scientific community and the public, the results will be presented in workshops, conferences, scientific journals, newspapers and various social media.
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