Preventing Data Tampering in Smart Grids: A Blockchain-Based Digital Twin Framework

As modern power systems evolve in complexity and dynamism, there arises a pressing need for innovative methodologies to streamline their management and optimization. Decentralization strategies, enabled by edge computing and Digital Twins (DTs), offer promising remedies to these issues by facilitating real-time interaction with physical systems and integrating data for advanced analytics, including predictive forecasting. While Smart Grids have emerged as efficient solutions for enhancing system performance and reducing costs, certain challenges persist. This paper proposes a novel blockchain-based system designed to counter data poisoning within the domain of energy forecasting in smart grids. Our framework not only ensures the integrity of data but also fortifies defenses against attacks aimed at disrupting data-driven applications. Validation in a practical energy forecasting scenario demonstrates the reliability and efficacy of our approach. Results demonstrate the feasibility of the approach while providing positive insights about the detection of attacks.