Deteriorated power system components have a higher probability of failure than new components. Still, reliability of supply analyses traditionally model all components of the same type with the same probability of failure, and thus neglects the effect of deteriorated components. This paper presents a methodology to integrate a condition dependent component probability of failure model into a power system reliability analysis. The component state is described by a semi-Markov process, and the paper shows how this, under reasonable assumptions, can be approximated by a Markov process. The Markov assumption simplifies the analysis and allows the model to include preventive retirement and be calibrated to statistical data. A case study using statistical data for Norwegian power transformers shows that, in the Norwegian power system, the proportion of failures that are due to poor condition is small, partly due to the common strategy of preventive retirement. However, if the condition of the transformers were worse, the impact of poor condition can be considerable. The methodology further enables identification of the transformers that contribute most to the risk to reliability of supply. The paper thus highlights the importance of accounting for component condition in strategic decisions such as long-term renewal planning.