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A Framework for Integrating Virtualized PAC into Availability Model of a Digital Substation: An Exploratory Adaptation of Software Aging and Rejuvenation Model

Submitted:

08 April 2026

Posted:

08 April 2026

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Abstract
Software aging and the corresponding need for system rejuvenation are well‑established concepts in computer science. As virtualization technologies are increasingly adopted within electric power utility infrastructures, early investigation into Software Aging and Rejuvenation (SAR) models, aging indicators, and empirical data collection becomes essential. Given the critical role of the electric power grid and the high dependability requirements of the protection and control systems that support its operation, proactive research in this area is timely and necessary. Motivated by this need, this work proposes a hierarchical framework that integrates an SAR model into the Reliability Block Diagram (RBD) representation of a Digital Substation Automation System (DSAS). The analysis shows that, for the selected parameter set, incorporating SAR into the VPAC reliability model results in higher estimated failure rates and increased annual downtime relative to hardware‑only models. When combined with substation primary system indices, however, the overall reliability indices remain largely unchanged, aside from reduced outage duration attributed to improved switching performance enabled by the DSAS architecture. Further examination reveals that the limited influence of SAR is primarily due to the lack of historical failure‑mode data for the secondary system. Availability of such empirical data is expected to significantly affect combined reliability indices and improve the accuracy of reliability evaluations. This highlights the importance of systematic data collection and aging‑indicator analysis as utility infrastructures transition toward virtualized and software‑dependent architectures.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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