Abstract
One of the most important components of smart grid digital substation is the merging unit (MU). A possibility to consider the MU as a recovered multi-state system (RMSS) is shown. It is also shown that the MU can be considered as a system, which consists of one “core” and one “shell”. The “core” of the MU is its part, which provides functions for performing analog-to-digital (digital) conversion. The “shell” of the MU is its part which provides synchronous measurements of vector functions. Existing approaches to RMSS assessment based on Markov models are considered. Degradation levels for MU are obtained and degradation diagrams (DD) are developed. On the basis of the DD, the models of RMSS availability with using Markov chains (MC) are proposed and analysed. The main feature of the proposed MC-based models is consideration of testing and recovery errors caused by problems of checking coverage and faults of checking means. The models also take into account two different preventive maintenance policies (PMP). According to the first policy (PMP1), preventive maintenance is performed through exponentially distributed time. According to the second one (PMP2), preventive maintenance is performed both through exponentially distributed time and when failures are detected in the current testing. The features of the models applications for RMSS with proposed PMP are shown. Recommendations based on the research results for improving maintenance policy and availability of the MU are formulated. Future research directions can be related to development of MC-based models for smart grid with two and more “core” and “shell”. Besides, development and research of smart grid models for cases of its components multiple failures are important as well.
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Fesenko, H., Kharchenko, V., Brezhnev, E., Zaitseva, E., Levashenko, V. (2017). Markov Models of Smart Grid Digital Substations Availability: Multi-level Degradation and Recovery of Power Resources Issues. In: Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (eds) Green IT Engineering: Components, Networks and Systems Implementation. Studies in Systems, Decision and Control, vol 105. Springer, Cham. https://doi.org/10.1007/978-3-319-55595-9_16
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DOI: https://doi.org/10.1007/978-3-319-55595-9_16
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