The seismic failure correlation among structures, systems and components(SSCs) in nuclear power plants(NPPs) is an important issue for evaluating the seismic risk of NPPs. In conventional seismic probabilistic risk assessment(PRA), it is common practice to assign complete correlation to redundant components while assuming zero correlation to other components, even though the actual correlation is likely to be partial. The impact of this assumption has been confirmed by the sensitivity analysis under the condition that zero correlation for the redundant components has been assumed. One of the challenges in considering seismic partial correlation is the evaluation method required to manage the large number of possible SSCs’ combinations. A possible solution is to utilize the direct quantification of fault trees using Monte Carlo simulation(DQFM) method, however it is not practical to handle large scale Fault Trees(FTs) of an actual NPP in the DQFM method. This paper presents a quantification approach which integrates the DQFM method with the Minimal Cutsets(MCSs) method. The presented approach enables to handle large scale FTs and to perform an evaluation considering seismic correlation. A case study of a hypothetical PWR plant, in which hundreds of components are considered, is conducted to demonstrate the applicability of this approach for seismic risk evaluation.