Wrong data identification and correction for WAMS

With the widely use of wide area measurement system (WAMS), data measured by PMU is becoming more and more important for real-time operation in power system. At present, error warnings and neglect of real alarms problems are produced in WAMS when considering the injection of wrong data. However, state estimation performs poorly in dealing with the wrong data in WAMS causing tremendous computation resources and time. In this paper, a rapid identification and recovery method based on the concept of pattern recognition is put forward. Without repeated iterations and the injection of parameters of power grid, all the wrong data can be easily and quickly identified by changing from feature space to pattern space. To support our conclusion, 90 samples in practical application of WAMS are processed, demonstrating the effectiveness of the proposed method.