The overall I-NERGY service analytics framework will be applied, implemented, demonstrated and validated in real-life pilots in 9 pilot hubs (15 use cases) across 8 countries.
The large geographical coverage of the demo sites aims to support the EU-wide replicability and market take-up of AI-driven solutions in different socio-economical contexts to maximize the impact of I-NERGY services across Europe. I-NERGY pilot’s approach will comprehensively test the analytics devised to cover the initially detected interests of relevant EPES stakeholders within the energy value chain, covering their whole energy market: from the operation and maintenance to the society, as well as cross-cutting interests, such as policy making and research. The energy sector will be considered from different perspectives: buildings as individual elements (building level) to their aggregation at varied scales (districts / communities) and territories. This holistic approach will enable to test the non-exhaustive set of I-NERGY open services which could be expanded by third parties through the Open Calls.
In each of the 9 pilots’ specific application and testing of the AI analytics devised in I-NERGY (representing different business models or situations among EPES stakeholders under 15 use cases) will be performed. Rationale of pilot applications is to address in a combined way two of the major challenges actually hindering AI analytics value capturing in the energy sector, i.e.,
- nurturing the shifting towards Predictive/prescriptive analytics and
- enabling multiple data source (cross –functional and/or cross-contexts and/or cross-domain) analytics for multiple applications.
In each of the pilots the interests of different EPES stakeholders will be pictured, as well as the perspective to the energy challenge at hand in each of them. Each one is led by the most representative EPES actor, bridging this way real problems encountered by these stakeholders in their everyday undertaking to I-NERGY solutions. In total three groups of holistic energy services will be developed, as explained below:
Pilot 1 [R&D NESTER - Portugal]
- Pilot 1/Use Case 1: AI for enhanced network assets predictive maintenance, integrating off-grid data with condition-based monitoring.
- Pilot 1/Use Case 2: AI for network loads and demand forecasting towards efficient operational planning.
Pilot 2 [VEOLIA - Spain]
- Pilot 2/Use Case 3: AI for energy demand prediction to optimize District Heating Network (DHN) operation.
Pilot 3 [ASM - Italy]
- Pilot 3/Use Case 6: Cross-functional AI-based predictive analytics to support integrated DSOs asset management and network operation.
Pilot 2 [VEOLIA - Spain]
- Pilot 2/Use Case 4: AI for energy saving verification service, increasing the trust on Energy Performance Contracts.
Pilot 3 [ASM - Italy]
- Pilot 3/Use Case 7: AI-based consumption and flexibility prediction for local community optimal aggregation and flexibility trading.
Pilot 4 [BFP - Italy]
- Pilot 4/Use Case 9: AI-based IoT-enabled PV module-level portfolio optimal predictive maintenance and PV-enhanced industrial plant optimal operation.
Pilot 5 [HERON/PARITY - Greece]
- Pilot 5/Use Case 10: AI in EV charging infrastructure.
Pilot 6 [ZEZcoop - Croatia]
- Pilot 6/Use Case 11: AI for peer-to-peer renewable energy trading in virtual energy community.
Pilot 2 [VEOLIA - Spain]
- Pilot 2/Use Case 5: AI for multi energy systems decision-support - Reina Sofia.
Pilot 3 [ASM - Italy]
- Pilot 3/Use Case 8: AI-based energy-driven and non-energy services.
Pilot 7 [SONCE - Slovenia]
- Pilot 7/Use Case 12: AI for the Ambient Assisted Living and personal safety/security at home
Pilot 8 [REA - Latvia]
- Pilot 8/Use Case 13: AI for energy efficiency investments de-risking
Pilot 9 [FAEN - Spain]
- Pilot 9/Use Case 14: AI for improved Energy Performance Certificates Reliability.
- Pilot 9/Use Case 15: AI for predicting the climate change impact in RES and energy demand at regional (local) level.