International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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A Novel AI-Blockchain-Edge Framework for Fast and Secure Transient Stability Assessment in Smart Grids

Author(s) Sree Lakshmi Vineetha Bitragun
Country United States
Abstract Safeguarding transient stability in today's electric power systems is key to ensuring grid reliability, especially as renewable energy sources, distributed generation, and cyber-physical interactions continue to expand. Conventional transient stability assessment (TSA) methodologies are predominantly reliant on numerical simulations, which are encumbered by excessive computational expenses, model simplifications, and restricted applicability in real-time scenarios. To tackle these difficulties, this study puts forth a novel hybrid approach that integrates AI-based forecasting, blockchain-supported data authentication, and edge computing to enable prompt transient stability analysis. The proposed AI model employs deep learning methodologies trained on historical transient event datasets to accurately predict stability margins with a high degree of precision. The incorporation of blockchain technology guarantees the integrity and security of TSA data, thereby alleviating risks associated with data manipulation or erroneous evaluations. Furthermore, an edge computing layer is implemented to conduct localized transient stability analyses, which substantially diminishes the latency typically linked with centralized processing. Comparative experiments reveal that the proposed methodology surpasses traditional numerical simulations and hybrid simulation tools such as HRTSim concerning accuracy, computational efficiency, and adaptability to real-time grid dynamics. This framework sets the precedent for the development of next-generation smart grids, in which transient stability can be dynamically assessed with augmented speed, security, and precision.
Keywords Transient Stability Assessment (TSA),Electric Power Systems (EPS),Artificial Intelligence (AI) in Power Systems, Deep Learning for Grid Stability, Blockchain for Secure Power Grid Validation, Edge Computing in Smart Grids, Hybrid Simulation for Power Systems
Field Engineering
Published In Volume 6, Issue 6, November-December 2024
Published On 2024-11-05
DOI https://doi.org/10.36948/ijfmr.2024.v06i06.38290
Short DOI https://doi.org/g86xs3
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