Abdullah Umar , Prashant Kumar Jamwal , Deepak Kumar , Nitin Gupta , Vijayakumar Gali , Ajay Kumar
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引用次数: 0
Abstract
This study proposes a decentralized, blockchain-enabled demand response (DR) framework to address the limitations of traditional centralized DR systems, which often suffer from privacy vulnerabilities, single points of failure, and susceptibility to Sybil attacks. By combining a hybrid Proof-of-Stake (PoS) mechanism with dynamic reputation scoring, the framework ensures secure and Sybil-resilient validator selection for consensus. To preserve privacy, Zero-Knowledge Proofs (ZKPs) ,SNARKs are embedded into smart contracts, enabling verifiable energy transactions without revealing sensitive bid or identity information. A dynamic game-theoretic model is used to capture the strategic interactions of prosumers during DR events, with formal analysis proving convergence to the Nash equilibrium under practical load conditions. The system is implemented using Solidity on the Polygon Mainnet and evaluated with real residential data from the Pecan Street dataset. Experimental results demonstrate significant performance gains, including a 12% reduction in peak demand, a 10% increase in prosumer generation, 83% load-shifting efficiency, and a 5.26% improvement in cost savings compared to static demand-side management (DSM) schemes. Additionally, the framework effectively mitigates 99% of Sybil attacks and achieves consensus within 8 s for up to 1000 nodes, highlighting its scalability, security, and suitability for integration with national DR platforms, carbon credit markets, and autonomous multi-agent energy systems.
期刊介绍:
Encouraging a transition to a sustainable energy future is imperative for our world. Technologies that enable this shift in various sectors like transportation, heating, and power systems are of utmost importance. Sustainable Energy Technologies and Assessments welcomes papers focusing on a range of aspects and levels of technological advancements in energy generation and utilization. The aim is to reduce the negative environmental impact associated with energy production and consumption, spanning from laboratory experiments to real-world applications in the commercial sector.