The existing analytic models for power system fault diagnosis generally only employ the state information of protective relays and circuit breakers，and the information redundancy is very limited.As the result，definite diagnosis results may not always be attained for complicated fault scenarios.The development of the phasor measurement unit（PMU）based wide area measurement system（WAMS）has generally made the acquisition of real-time and accurate electrical data possible.Given this background，the existing fault diagnosis analytic model is further developed with the electrical data from WAMS，and can be solved by the well-established genetic algorithm.Firstly，the fault areas are rapidly determined by using the combined data of states of circuit breakers and electrical data.Then，the fault diagnosis is carried out for the identified fault areas using the proposed analytical model.Finally，it is shown by simulation results of a sample system that the developed model is feasible and has good fault-tolerant capability.It can handle complicated fault scenarios with malfunctions of protective relays/circuit breakers as well as distorted/lost alarms.