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Data hub for the Creation of Energy communities at Local Level and to Advance Research on them

Periodic Reporting for period 2 - DATA CELLAR (Data hub for the Creation of Energy communities at Local Level and to Advance Research on them)

Reporting period: 2023-06-01 to 2024-11-30

The clean energy transition is an urgent priority in tackling climate change, requiring global solutions, coordinated policies, and strong collaboration between public and private entities across multiple sectors. Local Energy Communities (LECs) play a crucial role in this transition by promoting collective self-consumption, flexibility, and equitable access to energy services, while also integrating diverse market players into multi-vector energy markets. The increase in distributed energy generation, driven by higher adoption of renewable sources, has led to a decentralization of the energy value chain, positioning LECs and their innovative business models as key enablers in engaging citizens and local economic actors. Within this framework, and in alignment with the European Data Strategy, DATA CELLAR is developing an Energy Data Space to enhance Europe's energy competitiveness, sovereignty, and support LECs. The project’s goal is to unlock the full potential of energy-related data, facilitating the creation of new services and business models across different sectors. DATA CELLAR will implement a collaborative platform that provides an interoperable, secure, and federated energy data space. This platform will enable access to datasets, AI models, and decision-support tools, leveraging insights from previous EU projects. The DATA CELLAR data space will facilitate real-time and historical data sharing from private metering systems, while also integrating external data sources and EU-wide federated energy spaces. It will support energy utilities, energy communities, private businesses, and citizens, with validation through ) Validation Cases, each characterized by diverse regulatory, technological, and operational environments. The platform includes different tools:
- A Digital Twin for data-driven energy modeling.
- A comprehensive Decision Support System (DSS) for LEC planning and management, assisting energy utilities, DSOs, and technology providers in scenario evaluation.
- Environmental and economic assessment tools to enable real-time LCA (Life Cycle Assessment) and LCC (Life Cycle Costing) analysis for energy-related services.
- A data analytics and visualization platform to support energy analysts in designing data pipelines, leveraging machine learning and deep learning models.
- Additionally, DATA CELLAR will provide a decentralized, open marketplace for energy datasets and pre-trained AI models, fostering data monetization and exchange to support LECs.
A crucial element of the project is the Validation Case campaign, which will not only populate the data space but also test and refine the platform, AI services, Digital Twin, and DSS tools, ensuring they are robust, user-centric, and aligned with market needs.
Finally, DATA CELLAR is designed to be fully compliant and interoperable with major European initiatives, including Gaia-X and other sister projects, ensuring integration and scalability across the EU energy ecosystem.
During M13-M30, significant progress was made in developing the DATA CELLAR platform and its core components, focusing on data acquisition, interoperability, AI-driven services, decision-support tools, and federated energy data spaces integration.

WP3: The Common Data Model was refined for semantic interoperability (Gaia-X, IDSA), data acquisition and ingestion mechanisms were implemented (real-time/historical data, GDPR-compliant), and anonymization/aggregation modules ensured secure processing.

WP4: The ICT architecture was developed, the Common Data Environment (CDE) and federated catalogue are in progress, and SSI and Verifiable Credentials were implemented for secure authentication. The DATA CELLAR Connector, built on Eclipse Dataspace Connector (EDC), was integrated with the Identity Management system, enabling trusted decentralized data transactions.

WP5: AI/ML models were deployed for LECs, covering energy demand forecasting, PV production, anomaly detection, and flexibility estimation (beta version). NILM models were enhanced for household energy consumption disaggregation, explainability techniques were introduced, and Digital Twin & DSS tools were developed (beta versions).

WP6: The DATA CELLAR decentralized marketplace was designed, and discussions on governance rules were initiated.

WP7: The Validation Case campaign launched, involving 9 pilot sites in testing AI services, Digital Twin, DSS, and marketplace functionalities, with real-world energy data analysis ensuring regulatory alignment.

Interoperability & Data Federation: DATA CELLAR actively engaged in EU-wide initiatives (Omega-X, EDDIE, Enershare, SYNERGIES, INT:NET, BRIDGE). Federated data-sharing protocols were established for seamless external data exchange. SSI and Verifiable Credentials strengthened security, ensuring controlled access, data integrity, and transparency.

The next phase will fine-tune platform functionalities, expand real-world validation, and ensure full-scale deployment across EU energy ecosystems.
DATA CELLAR will develop an energy data space to support the development and the better management of Local Energy Communities all over Europe. One of the key achievements is the development of federated data-sharing protocols and a secure identity management system, ensuring trusted and seamless data exchange among multiple stakeholders. This interoperability framework, coupled with the DATA CELLAR Connector, strengthens the platform’s ability to integrate with existing and future energy data spaces, supporting the EU’s vision of a federated, decentralized digital infrastructure. The results achieved so far demonstrate the platform's potential in enhancing energy data accessibility, fostering interoperability across EU digital ecosystems. The project has made progress in advancing data-driven solutions for Local Energy Communities (LECs), integrating innovative AI services, decentralized data marketplaces, digital twins, and decision support tools. The integration of AI and machine learning models has also yielded promising outcomes, with advanced forecasting models for energy demand, renewable energy production, and flexibility estimation being deployed. The use of transfer learning for time-series data analysis represents a breakthrough in enhancing predictive capabilities while addressing the challenge of limited historical datasets.
The Digital Twin tool and Decision Support System (DSS) have provided data-driven insights into LEC development, supporting optimal RES sizing, flexibility assessment, and environmental impact analysis. These tools empower energy communities, municipalities, and DSOs by offering a structured approach to investment planning and grid optimization. Furthermore, the blockchain-based data marketplace introduces a fair token economy, allowing data providers to monetize their contributions while ensuring data sovereignty and privacy compliance. The marketplace’s integration with distributed ledger technologies enhances transparency, fostering trust among participants and enabling the development of sustainable, decentralized business models in the energy sector.
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