Electrical facilities in aging high-rise buildings face heightened safety risks due to prolonged operational aging, posing threats of power outages, fires, and electrocution. This study proposes a fuzzy Bayesian network-based risk assessment method. By constructing a Bayesian network topology mapping electrical failures to latent hazards and integrating fuzzy theory, the model quantifies failure probabilities and consequence severities. A risk matrix synthesizes these metrics to determine risk levels. Validated through a case study on transformer short-circuit hazards in a residential complex, the method demonstrates alignment with real operational conditions. The framework enables maintenance personnel to systematically identify hazards and implement risk-informed decisions, significantly enhancing electrical safety management in high-rise infrastructures.