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In power system reliability evaluation, usually component failures are assumed independent and reliability indices are calculated using methods based on the multiplication rule of probabilities. But in some cases, for instance when the effects of fluctuating weather are considered, the previous assumption is invalid. Generally, two kinds of methodologies are adopted to solve this problem, namely analytical and simulation. This paper proposes a DC-OPF based Markov cut-set method (DCOPF-MCSM) to evaluate composite power system reliability considering weather effects. The proposed method uses DC-OPF approach to determine minimal cut sets (MCS) up to a preset order and then uses MCSM to calculate reliability indices. In the second step, Markov process is applied, at a time, to the components of the determined MCS (and their unions) instead of the entire system. Since enumerating all MCS (and their unions) of a power system is impractical and unnecessary, this paper proposes an algorithm to calculate the bounds of reliability indices and it can automatically generate transition rate matrix (TRM) of the determined MCS (and their unions). The proposed method is tested on the modified IEEE Reliability Test System (RTS) and the results are compared with those of the next-event sequential simulation (NESS). The implementation demonstrates that the proposed method is effective and efficient and can conveniently incorporate more system operational considerations.