The electric power system is a critical infrastructure in which power transformers play a key role in linking together generation and end-use of electricity. The consequences of transformer breakdown can be significant, and aging transformers have a higher probability of failure. For decisions in asset management and power system development, it will therefore be useful to capture how deteriorating component condition affects failure probabilities and the overall reliability of the power system. Since such decisions have planning horizons of multiple years, the analysis should also capture similar time horizons. To this end, this paper proposes an analytical approach to power system reliability analysis (PSRA) accounting for time dependencies in the technical condition of components. An analytical PSRA methodology integrating a transformer condition model is extended to analysis horizons of multiple years. This analytical methodology is compared with a Monte Carlo simulation (MCS) approach to PSRA by applying both to a realistic case study. The comparison validates the analytical approach by showing that the inaccuracies its approximations introduce are negligible, at least for the considered case. This means that the proposed methodology can be a computationally viable alternative to MCS methods, especially when it is too time consuming to assess the impact of different scenarios with sufficient statistical precision using MCS. However, drawbacks with the analytical approach for further extensions of the methodology are also discussed.