This thesis first aims to investigate the effects of component repair on the availability, reliability and component importance analyses of various SASs. Due to the limitations and vagueness in the practical input data, the thesis then presents a technique to assess the reliability of SASs which reflects the impacts of input parameter uncertainties described by three types of fuzzy membership functions on the calculated reliability indices. In the next step, a new Markov model for SAS is proposed which reflects the impacts of control devices, protection functions, and communication networks. Thereafter, the thesis concentrates on an implementation of advanced fuzzy arithmetic into reliability assessment of SAS and proposes an advanced fuzzy-Markov model for SAS. Afterwards, a quantitative reliability evaluation of different automated industrial substations is performed. Subsequently, a composite reliability assessment model of distribution system is presented which illustrates the impacts of substations automated by various automation configurations on the reliability of the primary distribution systems equipped with a specific distribution automation scheme. Finally, a technique is proposed to assess the reliability of composite generation and transmission system reliability which reflects the impacts of SAS and automated substations on the calculated reliability indices. Key Words Automated industrial substation, availability, fuzzy set, Markov model, reliability block diagram, substation automation system.