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Human operators play a key role in the reliable operation of critical infrastructures. However, human operators may take actions that are far from optimum. This can be due to various factors affecting the operators’ performance in time-sensitive and critical situations such as reacting to contingencies with significant monetary and social impacts. In this paper, an analytic framework is proposed based on Markov chains for modeling the dynamics of cascading failures in power grids. The model captures the effects of operators’ behavior quantified by the probability of human error under various circumstances. In particular, the observations from historical data and information obtained from interviews with power-system operators are utilized to develop the model as well as identify its parameters. In light of the proposed model, the noncritical regions of power-system's operating characteristics with human-factor considerations are characterized under which the probability of large cascading failures is minimized. [ABSTRACT FROM AUTHOR]