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Beyond Traditional Grid: A Novel Quantitative Framework for Assessing Automation’s Impact on System Average Interruption Duration Index and System Average Interruption Frequency Index
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Journal Article
Beyond Traditional Grid: A Novel Quantitative Framework for Assessing Automation’s Impact on System Average Interruption Duration Index and System Average Interruption Frequency Index
2025
Overview
The existing literature on power grid reliability extensively examines the effects of individual automation technologies, such as Smart Grids, IoT, and AI, on reducing SAIDI (System Average Interruption Duration Index) and SAIFI (System Average Interruption Frequency Index) indices. However, previous studies have largely focused on partial analyses, often limited to specific aspects of grid operation or isolated case studies. As a result, there is a lack of a comprehensive and integrated theoretical approach that considers the interdependencies between different automation technologies, their impact on various levels of grid management and the economic consequences of their deployment. This study presents a novel theoretical framework aimed at providing a holistic perspective on power grid automation and its impact on energy supply reliability. The key elements of this approach include developing a multidimensional mathematical model that integrates the impact of key automation technologies on SAIDI and SAIFI, allowing for a quantitative assessment of different implementation strategies and applying a probabilistic approach to predict the likelihood of power outages based on the level of automation and real-time grid conditions. This proposed framework offers a holistic view of power grid automation, integrating technical, economic and operational dimensions. It serves as a foundation for further empirical research and the implementation of intelligent grid modernisation strategies, aiming to enhance power supply stability and increase the resilience of distribution networks against outages. The introduced concept aligns with the current challenges of the energy transition, providing utilities and policymakers with analytical tools for making optimal decisions regarding the adoption of digitalisation and automation technologies in the power sector.
Publisher
MDPI AG
Subject
