The project “Smart Integration of Energy Storages in Local Multi Energy Systems for maximising the Share of Renewables in Europe’s Energy Mix” (SmILES) is a joint project with AIT, DTU, EDF SA (and EIFER EWIV), Vito/EnergyVille and EERA AISBL. SmILES zooms in simulation and optimisation of smart storage in local energy systems for increasing the understanding and transparency of innovative multi-energy projects. Setting up a shared data and information platform and effective dissemination of related results will contribute to competence building. Supplementing the research activities, a long-lasting framework across EERA JP borders has been set up by the consortium for extending storage integration technologies by linking other EERA members, stakeholders, energy supplier and industry.
The SmILES proposal contributes to the “European Common Research and Innovation Agendas (ECRIAs) in support of the implementation of the SET Action Plan” (LCE 33). The objective of SmiLES is twofold:
- Obtaining fundamental knowledge about linking and optimising heterogeneous energy carriers and systems including storage and renewable energy technologies across geographical scales from local to national.
- For the European level: Development and dissemination of guidelines for modelling, simulating and optimising such systems. These guidelines will be derived from aggregated and merged knowledge of five different energy system configurations, which combine heat- and electrical power systems with storage capabilities (CHPS).
SmILES' objectives are compliant with ECRIA's, as national research efforts are largely integrated and still existing gaps in the deployment of hybrid energy systems can be identified. It creates synergies at EU and national levels and avoids duplication of efforts. Additionally SmILES will point out opportunities of joining the information, communication and physical technologies in the energy domain, especially in flexible thermal and electrical energy generation, demand side response and storage, as well as efficient heating and cooling technologies. It will depict synergies between energy vectors and demand analysis, including at least partially the exploitation of Big Data methods.