Analyzing Substation Automation System Reliability using Probabilistic Relational Models and Enterprise Architecture

Modern society is unquestionably heavily reliant on supply of electricity. Hence, the power system is one of the important infrastructures for future growth. However, the power system of today was designed for a stable radial flow of electricity from large power plants to the customers and not for the type of changes it is presently being exposed to, like large scale integration of electric vehicles, wind power plants, residential photovoltaic systems etc. One aspect of power system control particular exposed to these changes is the design of power system control and protection functionality. Problems occur when the flow of electricity changes from a unidirectional radial flow to a bidirectional. Such an implication requires redesign of control and protection functionality as well as introduction of new information and communication technology (ICT). To make matters worse, the closer the interaction between the power system and the ICT systems the more complex the matter becomes from a reliability perspective. This problem is inherently cyber-physical, including everything from system software to power cables and transformers, rather than the traditional reliability concern of only focusing on power system components. The contribution of this thesis is a framework for reliability analysis, utilizing system modeling concepts that supports the industrial engineering issues that follow with the implementation of modern substation automation systems. The framework is based on a Bayesian probabilistic analysis engine represented by Probabilistic Relational Models (PRMs) in combination with an Enterprise Architecture (EA) modeling formalism. The gradual development of the framework is demonstrated through a number of application scenarios based on substation automation system configurations. This thesis is a composite thesis consisting of seven papers. Paper 1 presents the framework combining EA, PRMs and Fault Tree Analysis (FTA). Paper 2 adds primary substation equipment as part of the framework. Paper 3 presents a mapping between modeling entities from the EA framework ArchiMate and substation automation system configuration objects from the IEC 61850 standard. Paper 4 introduces object definitions and relations in coherence with EA modeling formalism suitable for the purpose of the analysis framework. Paper 5 describes an extension of the analysis framework by adding logical operators to the probabilistic analysis engine. Paper 6 presents enhanced failure rates for software components by studying failure logs and an application of the framework to a utility substation automation system. Finally, Paper 7 describes the ability to utilize domain standards for coherent modeling of functions and their interrelations and an application of the framework utilizing software-tool support.