This paper introduces the EU-DREAM initiative, which combines Blockchain/Distributed Ledger Technology (DLT) and Digital Twin (DT) to achieve secure, transparent, and consumer-centric energy services. We discuss the high-level system architecture, emphasising how DLT ensures data integrity and how DT enable real-time scenario and historical analysis with DLT integrity-certified data for users. We describe the core platform layers, detail the blockchain–digital twin integration, and present application scenarios focusing on community-scale energy trading, demand flexibility, and microgrids. We conclude with a discussion of future development steps and the challenges of ensuring privacy, scalability, and compliance with EU data regulations.

Decentralised energy ecosystems suffer from data-governance, scalability and adoption barriers. Although blockchain-based marketplaces can offer transparency and security in Local Energy Communities (LECs), most existing solutions struggle with rigid token models, limited performance, and steep usability barriers. Building on a previous framework, this study presents an enhanced marketplace that integrates a modular blockchain layer, custodial identity management, and a dual-token model for flexible licensing and pricing. Testing on a per-missioned Quorum network with asynchronous queueing demonstrated notable improvements in transaction throughput and user responsiveness under load, while the custodial onboarding flow simplified access for non-technical participants. A refined policy enforcement mechanism further aligns the system with emerging federation standards, mitigating earlier shortcomings related to performance, data sovereignty, and scalability. Benchmarking on a five-node Quorum Proof of Authority (PoA) deployment (one RPC node and four validator nodes) showed that all key operations, including license issuance and asset usage, consistently completed in under 8 seconds, confirming the system’s suitability for possible energy data applications. Planned extensions include cross-domain interoperability, self-service governance tools, and zero-knowledge proofs, underscoring this architecture’s potential as a robust, future-ready platform for federated energy data ecosystems.

Decentralised Autonomous Organisations (DAOs) face a recurring challenge in maintaining active, high-quality participation among their members. Voter apathy and strategic abstentions undermine the collective intelligence that DAOs aim to harness. This paper proposes a game-theoretic incentive model, specifically tailored to encourage sustained participation in DAO governance. By combining a reputation-based mechanism with monetary rewards (e.g., token incentives), the model aligns individual actions with the collective good, penalising prolonged inactivity and rewarding long-term collaboration. We describe how key parameters, such as reputation thresholds and rewards for voting, can be calibrated to preserve a DAO’s vitality and avert excessive concentration of power. Simulations in a community-energy scenario demonstrate the feasibility of the approach and provide insights into balancing tolerance for occasional abstentions with the need for consistent governance engagement. Ultimately, our results indicate that with carefully chosen parameters, DAOs can maintain high participation rates and secure more robust decision-making over time.

This paper introduces a user-friendly tool designed to simplify smart contract analysis through a microservice architecture implemented in Golang and Flutter. The system combines four primary components: a Codec for contract encoding/decoding, an Auditor powered by Slither for security assessment, a Database for version control, and an AI Assistant leveraging gpt-3.5-turbo from OpenAI for automated annotations. User interaction is facilitated through UML-based visual representations that allow intuitive comprehension of the smart contract implementation. An evaluation through the NASA-TLX questionnaire demonstrated that the proposed tool could significantly reduce the overall workload (52.62 versus 71.74) compared to Remix IDE, with notable improvements in mental demand, temporal demand, and frustration levels.

In an era of digital proliferation, especially in energy and AI sectors, this study introduces a blockchain-based framework to enhance data exchange and utilization. This infrastructure, grounded in a decentralized Data Marketplace on a blockchain network, ensures secure and transparent interactions among stakeholders while managing real-world data with a federated architecture compliant with regulations. By integrating connector technology for uniform platform interaction and utilizing smart contracts for autonomous transactions, this solution advances data integrity and intellectual property management through NFTs and datatokens. Here, energy data within the blockchain represents intellectual property managed by multiple parties, symbolized as NFTs and licensed through datatokens (ERC-20 tokens). This approach enhances security, efficiency, and scalability in energy and AI data sharing, showing potential to foster collaboration and innovation.