Artificial Intelligence (AI) is expected to radically transform the energy sector, redesign and shape the energy value chain and revolutionise the way in which Electric Power and Energy Systems (EPES) community is undertaking business processes. The use of AI is acknowledged to be of utmost importance for energy utilities to improve the performance of their business processes, and for power network operators to increase the stability of their network, within the renewable energy-based emerging decentralised paradigm.
At the same time, AI proliferation in the energy sector holds the premise for a larger environmental and social impact, by affecting environmental sustainability, strengthening social relationships among members of local communities and contributing to alleviate energy poverty. Energy fingerprinting might be leveraged to deliver different consumer-centred innovative AI-based services which bring a quite high social value to individuals and/or local communities. Hence, AI can contribute to finding solutions to some of the most pressing societal challenges, such as the fight against climate change, environmental degradation and the challenges linked to sustainability.
In this context, the constantly increasing momentum of AI, Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL) represents an unprecedented opportunity for the EPES community, aiming at increased grid flexibility, optimised maintenance and/or optimal operation, as well as delivering social-oriented consumer-centred services at the interplay of energy efficiency, energy management, personal comfort, green energy purchasing, cross-sector energy vs mobility, and energy fingerprinting based social services (e.g. personal safety / security and AAL care management).
The overall vision of I-NERGY is to deliver an energy-specific open modular framework for supporting AI-on-Demand in the energy sector (AI4 Energy), by capitalising on state-of-the-art AI, as well as IoT, semantics and data analytics technologies. I-NERGY provided AI-based cross-sector multistakeholder analytic tools for integrated and optimised smart energy management, based on seamless data/information/knowledge exchange under respective sovereignty and regulatory principles. I-NERGY aims at evolving, scaling up and demonstrating innovative AI-as-a-Service (AIaaS) Energy Analytics Applications, which will significantly contribute to achieve a techno-economic optimal management of the EPES value chain, especially for SMEs and non-tech industries, while leveraging on and complementing the AI resources and tools made available by the AI4EU platform.
On top of the I-NERGY framework, the project defines AI energy analytics services and digital twins (grouped under the ‘Energy Commodities Networks’, ‘Distributed Energy Resources’ and ‘Energy Efficiency and Non-energy related Services’ categories) that were developed and tested within 9 pilot hubs (including 15 use cases). Moreover, state-of-the-art AI business cases and services were created, considering the interaction of different EPES stakeholders and software developers via the I-NERGY Open Calls that selected 25 Technology Transfer projects led by SMEs [under Financial Support to Third Parties (FSTP)]. I-NΕRGΥ’s vision is summarised in clear, measurable, realistic and achievable objectives, divided into 2 main categories:
(O1) Reinforce the service layer of the AI-on-demand-platform.
(O2) Reach out to new user domains and boost the use of the platform through use cases and small-scale experiments.
