I. Introduction
WITH the development of electric power system, the scale of power grid continues to expand. AC/DC transmission systems operate in parallel, and the development of UHV transmission system has become an inevitable trend [1]–[3]. Many FACTS equipments have been designed and applied into the power network. All of these make modern electric power system to develop in a high voltage, large scale, and intelligent direction. But, faults happen continuously in power network all over the world [4]. Some of them may result in terrible consequences. Simulation experiment is the most important method to analyze realistic faults, by which the complicated operation of real network can be simulated in laboratory. Simulation experiment has characteristic of security and economy. Simulation recurrence of realistic faults is helpful for operators to analyze the reason of faults and transient over-voltage and over-current in network. And simulation recurrence of realistic faults will supply a strong foundation for avoiding the same type faults and making correct limitation and protection measures. Therefore, the interest is specially focused on the study of power system simulation experiments. But up to now, based on many current simulation tools, the simulation results of realistic faults are not satisfying [5]–[9]. In the years of 2004 and 2005, twice large disturbance tests were carried out in Northeast China Power Gird, and dynamic operating process was recorded during the disturbance tests. In the subsequent simulation experiments, the veracity of simulation results has been improved in some extent through adjusting simulation models and parameters. But, the simulation results are quite different with the fault recordings [10]. It is a tough task to ensure an accurate reproduction of realistic faults by power system simulation experiments. In particular, the analysis of simulation errors depends on sightings mainly, which has a large degree of subjectivity. It is urgent to measure simulation errors, and to establish a complete evaluation theory of simulation errors.