Obiettivo
Data Centres (DC) are among the largest yet increasing energy consumers, due to the rising digitization of human activities. RES integration and energy efficiency improvements have the potential to reduce significantly DC carbon footprint, while increasing at the same time the auto-consumed energy, thus improving DC security and resiliency of supply against climate change. However, very few solutions, despite validated in lab, have been successfully deployed on operational DCs, mostly due to technological fragmentation, excessive CAPEX and lack of appropriate business models. CATALYST will address these challenges through turning existing/new DCs into flexible multi-energy hubs, which can sustain investments in RES and energy efficiency by offering mutualized flexibility services to the smart energy grids (both electricity and heat grids). By leveraging on the outcomes of FP7 GEYSER and DOLPHIN projects, CATALYST will adapt, scale up, validate and deploy an innovative, adaptable technological and business framework aimed at i) exploiting available DC non-IT legacy assets (onsite RES/backup generation, UPS/batteries, cooling system thermal inertia, heat pump for waste heat reuse) to deliver simultaneous energy flexibility services to multi-energy coupled electricity/heat/IT load marketplaces ii) deploying Cross-DC cross-infrastructures (e.g. heat vs IT) IT workload orchestration, by combining heat-demand driven HPC geographical workload balancing, with traceable ICT-load migration between federated DCs to match IT demands with time-varying on-site RES (“follow the energy approach”) iii) providing marketplace-as-a-service tools to nurture novel ESCO2.0 business models. The adaptation and replication potential of CATALYST will be demonstrated through carrying out four different real life trials spanning through the full spectrum of DCs types (fully distributed DCs, HPC, co-location, legacy) and architectures (from large centralized versus decentralized micro-DCs).
Campo scientifico (EuroSciVoc)
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
- ingegneria e tecnologiaingegneria ambientaleenergia e carburantienergia rinnovabile
- ingegneria e tecnologiaingegneria meccanicaingegneria termodinamica
- scienze naturaliscienze biologichezoologiamammologiacetologia
- scienze socialieconomia e commercioeconomia e gestione aziendalemodelli aziendali
- scienze naturaliscienze chimichecatalisi
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Programma(i)
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Vedi altri progetti per questo bandoBando secondario
H2020-EE-2017-RIA-IA
Meccanismo di finanziamento
IA - Innovation actionCoordinatore
00144 Roma
Italia