Reliability of multi-channel IEC 61850 mission-critical substation communication networks based on Markov process incorporating linear dynamical systems and calculus inferences.

Abstract

IEC 61850 based Substation Communication Networks (SCN) enable substation processes to be digitalised to fulfil the most sought substation monitoring, protection and control of electrical systems. The standard enables peer-to-peer communication of mission critical messages, aided by onboard diagnostic capabilities to ease the identification of system faults. The implementation of Safety-Related Systems in industrial facilities comprising sensors, logic solvers and final elements in power distribution centres necessitate compliance to IEC 61508 standard, where circuit breakers act as final elements to isolate electrical machines. In recent times, combinatorial methods such as the Reliability Block Diagram have been used to evaluate the architecture of IEC 61850 based SCN reliability and availability due to the simplicity of the approach. These methods, however, assume that all system faults are identified and fully repaired, which is not the case in practice. In this thesis, the reliability of a repairable multi-channel IEC 61850 based SCN architecture is modelled using a structure function and the Markov process while Systems Thinking integrates imperfect repair factors into the model. Thereafter, a novel eigenvalue analysis method based on Markov partitions and symbolic dynamics in the context of linear dynamical systems is used to investigate the impact of imperfect repairs on the system's reliability based on the number of mean state transitions and dynamical behaviour. The eigenvalue method is then advanced by a complimentary analysis technique based on the absorbing Markov Chain process and matrix calculus methods to determine the system's responsiveness to repair factors. The case studies results demonstrate that imperfect repairs cannot be ignored for mission-critical applications because the simplifying assumptions of combinatorial analysis methods greatly over-state the system's reliability performance. The results also indicate that common causes of failure coupled with imperfect repairs significantly negatively impact the system's performance. Moreover, system performance is highly dependent on the diagnostic coverage of the individual subsystems than their repair efficiencies for high diagnostic coverages at 90% and 99% based on ISO 13849-1. Hence, the results demonstrate that emphasis should be more on the system diagnostic coverage for the fact that it is embedded in the system design itself that cannot easily be changed once the system is commissioned and operational.