The deployment of small-scale renewable energy sources will transform the management of energy grids towards more decentralized solutions in which the prosumers will have a more active role. Regulatory and market barriers are driving the implementation of virtual aggregation models in which the small-scale prosumers work together on a larger scale to gain benefits that could not be obtained on an individual basis. In this paper, we propose to use public blockchain and self-enforcing smart contracts to construct Virtual Power Plants (VPPs) of prosumers to provide energy services. A model has been defined for capturing the prosumer level constraints in terms of available energy profiles and energy service requirements enabling their optimal aggregation in hierarchical structures. A lightweight decentralized solution for VPPs construction is implemented using smart contracts enabling its efficient running on the public blockchain. Smart contracts are encoding the model constraints and are defining functionalities for prosumers to initiate or join a VPP implementing the complete chain of Offer-Operate-Measure-Remunerate actions. The VPP will be managed on top of a distributed ledger technology offering decentralized functionality for tracking and validating the delivery of energy based on the blockchain transactions and for energy and financial settlement, the remuneration being done according to the amount of energy provided by individual prosumers. Experimental results show that the proposed solution runs successfully on the public blockchain with good execution time and can address Balancing Responsible Party requests for additional generation. The overhead in terms of gas consumption and transactional throughput stays within reasonable boundaries.

To ensure the success of energy transition and achieve the target of reducing the carbon footprint of energy systems, the management of energy systems needs to be decentralized. Public blockchains offer favorable features to support energy sector democratization and reinforce citizens’ trust, such as tamper-proof energy data registration and sharing, decentralization, transparency, and support for peer-to-peer (P2P) energy trading. However, in blockchain-based P2P energy markets, transactional data are public and accessible, which raises privacy concerns related to prosumers’ energy profiles while lacking scalability and featuring high transactional costs. In this paper, we employ secure multi-party computation (MPC) to assure privacy on a P2P energy flexibility market implementation in Ethereum by combining the prosumers’ flexibility orders data and storing it safely on the chain. We provide an encoding mechanism for orders on the energy market to obfuscate the amount of energy traded by creating groups of prosumers, by splitting the amount of energy from bids and offers, and by creating group-level orders. The solution wraps around the smart contracts-based implementation of an energy flexibility marketplace, assuring privacy features on all market operations such as order submission, matching bids and offers, and commitment in trading and settlement. The experimental results show that the proposed solution is effective in supporting P2P energy flexibility trading, reducing the number of transactions, and gas consumption with a limited computational time overhead.

Blockchain and tokens are relatively new research areas insufficiently explored from both technical and economic perspectives. Even though tokens provide benefits such as easier market access, increased liquidity, lower transaction costs, and automated transactional process, their valuation and price determination are still challenging due to factors such as a lack of intrinsic value, volatility, and regulation making trading risky. In this paper, we address this knowledge gap by reviewing the existing literature on token creation and valuation to identify and document the factors affecting their valuation, investment, and founding, as well as the most promising domains of applicability. The study follows the PRISMA methodology and uses the Web of Science database, defining clear research questions and objective inclusion criteria for the articles. We discuss token technical development, including creating, issuing, and managing tokens on an Ethereum blockchain using smart contracts. The study revealed several key factors that significantly impact the field of tokenomics: demand and supply, social incentives, market conditions, macroeconomics, collective behavior, speculation, and inclusion in index funds. The most relevant use cases of blockchain and tokens are related to the digitization of virtual and physical assets, accountability, and traceability usual in smart grids or supply chains management, social governance, and art and gamification including metaverse.

Within energy communities, the prosumers can engage in peer-to-peer trading, fostering local collaborations and increasing awareness about energy usage and flexible consumption. However, even under these favorable technological and organizational mechanisms, prosumer engagement levels remain low, requiring trading mechanisms that are aligned with their social values and expectations. In this paper, we introduce an innovative hedonic game coordination and cooperation model for peer-to-peer (P2P) energy trading among prosumers which considers the social relationships within an energy community to create energy coalitions and facilitate energy transactions among them. A heuristic is defined to optimize the prosumers’ coalitions, considering their social and price preferences while balancing the energy demand and supply within the community. The proposed hedonic game model was integrated into a state-of-the-art blockchain-based P2P energy flexibility market and evaluated its performance within an energy community of prosumers. The evaluation results demonstrate the effectiveness of considering social factors when creating coalitions, resulting in a 5% increase in the total amount of energy transacted in a market session compared to other game theory-based solutions and a degree of satisfaction varying between 91-96%. The results underscore the importance of the social dimensions of P2P energy trading, the positive social dynamics within the energy community leading to an even greater increase in energy transacted around 30%, potentially generating daily savings between ${\$}$ 34 and ${\$}$ 47 and additional carbon savings of approximately 15.4 kgCO2eq.

E13021 Background: Leptomeningeal metastases are rare but fatal manifestation of metastatic breast cancer, especially in HER2 positive sub-type, with limited treatment options and median overall survival in the range of only 4-6 weeks in untreated patients. Methods: Our prospective study included 9 patients with HER2 positive breast cancer with leptomeningeal metastases that received intrathecal treatment with Trastuzumab along with systemic therapy. Data was compared with a control lot of 9 patients with leptomeningeal metastasis that did not receive intrathecal treatment. Radiotherapy was administered in all patients. The patients included in the study received cures of 150 mg of Trastuzumab injected intrathecal every 3 weeks. Results: Median age of the patients at the time of diagnosis was 53 years. Median time from diagnosis of BC until diagnosis of leptomeningeal carcinomatosis was 3.4 years. Median progression free survival for patients receiving trastuzumab intrathecal was 11.1 months compare with 6.4 months in patients receiving standard treatment, p < 0.019. In our lot of patients, response rate was 66.6%. A clinical benefit with symptoms relief was observed in 77.7% of patients. Mean number of administrations was 12. Two patients presented pain and in two instance the administration was not possible. Concurrent systemic treatment consisted in lapatinib and capecitabine (22.2%), trastuzumab emtansine (44.5%), tucatinib combination (22.2%), vinorelbine (11.1%) and no unexpected toxicity to systemic treatment was noticed. Conclusions: Intrathecal administration of trastuzumab along with systemic treatment and radiotherapy, might improve or stabilise the consequences of leptomeningeal involvement by HER2-positive breast cancer with manageable toxicity.

The coordination of distributed grid-forming inverters is challenging because independently owned resources must achieve system-level stability and power-sharing objectives using decentralized, and potentially malicious information about local capabilities and operating conditions. In this paper, we address this problem by introducing a decentralized coordination mechanism that combines AI agents, blockchain-based smart contracts, and physics-informed validation. Each AI agent, representing a specific grid-forming inverter, declares the inverter's expected power contribution for each coordination epoch, while smart contracts enforce the coordination rules and maintain an immutable record of declared and observed behaviour. A physics-based detection mechanism, combining cumulative-sum change detection with feeder-level physical constraints, identifies deviations between the agent's declarations and the associated inverter's physical behaviour without interfering with real-time stability dynamics. The AI agents are linked to their corresponding physical inverters through an ERC-8004-based identity and reputation layer offering a verifiable on-chain identity and enabling accountability and adaptive reduction of the inverter's contribution when misbehaviour is detected. Evaluation results using the PTProsumer dataset show that coordination reduces the mean absolute frequency deviation from 133 to 47 mHz under honest operation. When two of four malicious agents collaborate, detection reduces the deviation from 223 to 80 mHz, while incorporating declared uncertainty reduces false penalties from 18 to 6 per day. Experiments with up to 100 inverters demonstrate manageable computational and blockchain overhead.