Periodic Reporting for period 2 - I-NERGY (Artificial Intelligence for Next Generation Energy)
Período documentado: 2022-07-01 hasta 2023-12-31
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.
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.
I-NERGY has reinforced the AI-on-Demand platform with more than 90+ assets including datasets, ML models, code, services and applications for the EPES sector. The assets can be accessed in the following url:
https://www.ai4europe.eu/ai-community/projects/i-nergy?category=ai_assets(se abrirá en una nueva ventana)
More specifically it has delivered the upgraded versions of the I-NERGY, visualization engine, Digital Twin for Electrical Communities service, Digital Twin for DER service, and Electrical load forecasting have been developed and deployed. DeepTSF, which offers codeless time series forecasting and facilitates AI model training from a wide variety of algorithms and configuration options, has been developed. Additionally, Flexibility Forecasting and demand response, the Energy Efficiency Investments Decision Support service, the District Heating Energy forecasting, and AI-enabled multi-energy systems decision support have been developed and deployed. Other significant developments include the I-NERGY Workbench, B2B Cross-stakeholder Trusted Off-chain Data Sharing and Re-use, the Interoperability and Harmonization module, the Streaming module, the Predictive Maintenance service, the Transfer Learning Wizard (TLWizard), and the IAM security component within the I-NERGY ecosystem and tools.
The I-NERGY services have been validated in 15 real-life pilots, while evaluating user satisfaction and effectiveness.
Two successful Open calls have been launched followed by the successful completion and showcasing of 25 Technology Transfer Projects (TTPs) bringing AI innovations in the EPES sector. Extensive communication efforts led to a significant digital presence, with workshops, talks, and publications highlighting the project's impact.
https://www.ai4europe.eu/ai-community/projects/i-nergy?category=ai_assets(se abrirá en una nueva ventana)
More specifically it has delivered the upgraded versions of the I-NERGY, visualization engine, Digital Twin for Electrical Communities service, Digital Twin for DER service, and Electrical load forecasting have been developed and deployed. DeepTSF, which offers codeless time series forecasting and facilitates AI model training from a wide variety of algorithms and configuration options, has been developed. Additionally, Flexibility Forecasting and demand response, the Energy Efficiency Investments Decision Support service, the District Heating Energy forecasting, and AI-enabled multi-energy systems decision support have been developed and deployed. Other significant developments include the I-NERGY Workbench, B2B Cross-stakeholder Trusted Off-chain Data Sharing and Re-use, the Interoperability and Harmonization module, the Streaming module, the Predictive Maintenance service, the Transfer Learning Wizard (TLWizard), and the IAM security component within the I-NERGY ecosystem and tools.
The I-NERGY services have been validated in 15 real-life pilots, while evaluating user satisfaction and effectiveness.
Two successful Open calls have been launched followed by the successful completion and showcasing of 25 Technology Transfer Projects (TTPs) bringing AI innovations in the EPES sector. Extensive communication efforts led to a significant digital presence, with workshops, talks, and publications highlighting the project's impact.
I-NERGY envisions becoming the product that will revolutionize the exploitation of AI analytics and data technologies in the activities and businesses related to energy, by providing a definitive framework for knowledge extraction, as well as fine-grained business intelligence services to interested EPES stakeholders. I-NERGY will continue to reinforce the AI-on-demand platform with state-of-the-art AI technologies for the EPES sector. I-NERGY has significantly influenced the financial and technical sectors by promoting the adoption of AI-as-a-Service (AIaaS) in the energy industry. By developing and disseminating innovative business models, I-NERGY has facilitated collaboration among industry stakeholders, aiding SMEs in discovering new revenue opportunities and ensuring their financial sustainability. The project has initiated structured processes for continued Open Calls, supporting SMEs in creating novel energy use cases and technology foundations. Additionally, I-NERGY partners have identified commercialization pathways and established relationships with industry partners, aiming to transition successful prototypes into scalable, market-ready solutions.
On the environmental and societal fronts, I-NERGY has been instrumental in advocating for energy efficiency and community engagement. By promoting AI applications that optimize grid management and renewable energy use, the project supports the transition to sustainable energy practices. Furthermore, I-NERGY has fostered technology and knowledge transfer, contributing to the adoption of interoperability standards for AI in the energy sector. The project has also explored cross-domain application scenarios, enhancing community engagement and ensuring inclusivity. By adhering to ethical AI practices, I-NERGY underscores the importance of transparency, accountability, and fairness in algorithmic decision-making, influencing the broader ecosystem to follow suit.
On the environmental and societal fronts, I-NERGY has been instrumental in advocating for energy efficiency and community engagement. By promoting AI applications that optimize grid management and renewable energy use, the project supports the transition to sustainable energy practices. Furthermore, I-NERGY has fostered technology and knowledge transfer, contributing to the adoption of interoperability standards for AI in the energy sector. The project has also explored cross-domain application scenarios, enhancing community engagement and ensuring inclusivity. By adhering to ethical AI practices, I-NERGY underscores the importance of transparency, accountability, and fairness in algorithmic decision-making, influencing the broader ecosystem to follow suit.