Due to limitation of economics and legislation, the power system is not allowed serious accident on modern social. In order to enhance system reliability, many types of special protection systems (SPS) have been implemented by utilities around the world. One of the main concerns in the design of an SPS is whether the designed system can achieve the reliability requirement. Currently, the literature that discusses the SPS reliability issue is scarce. In this thesis, a comparison of several techniques suitable for performing reliability assessment of SPS is presented. Discussed reliability models include using reliability block diagram, fault tree analysis, Markov modeling and Monte Carlo simulations. In order to understand the uncertainty effects of input data on the calculated system reliability, Monte Carlo Sampling method is utilized in this study to take the input parameters uncertainty into account in the system modeling. To deal with the problem of not being able to reach the reliability requirement after uncertainty analysis, a sensitivity analysis is proposed to analyze the importance of the components involved in the system. Sensitivity analysis can be used to identity the most effective component in the enhancement the SPS reliability. A Taipower SPS is used in this thesis to explain the proposed reliability assessment methods.