The electrical power grid is one of the most important infrastructures in the modernsociety. It supplies industrial and private customers with electricity and supportsother critical infrastructures such as the water supply. Thus, it is significant that the power grid is a reliable system. However, the power system experiences a hugetransition from classical production methods such as coal and nuclear power plantsto distributed renewable energy forms such as wind energy and photovoltaic. This change to a more distributed system challenges the existing power grid as well as the traditional business models of electric utilities. Thus, cost minimization to increase profitability and improvement of the power grid to increase customer satisfactionare in the focus. One approach to increase the reliability of the grid and decrease maintenance costs is a condition-based maintenance approach which requirescondition monitoring techniques. This thesis introduces into failure rate modelling for individual power system components and develops a method to calculate individual failure rates based onthe average failure rate, failure statistics, and condition monitoring data. This approach includes the analysis of failure statistics to identify failure causes and failure locations which are population characteristics but can be utilized to describe the heterogeneity within the population. Thus, the thesis first introduces into the topic of failure analysis and heterogeneity in populations. Different factors are identified and categorized which describe the condition development of a component overtime. Then, the literature within failure rate estimation is reviewed to present the factors which are used within failure rate modelling and to outline the existingmethods which consider the individual. However, limitations are discussed which emphasize the demand for a new approach. Consequently, this thesis introduce intoa new approach for estimating the failure rate for individual components. / <p>QC 20160526</p> / Energiforsk AB risk analysis program