A data-driven PMU bad data detection algorithm based on spectral clustering using single PMU data is described. The described algorithm does not require the system topology and parameters. First, a data identification method based on a decision tree is described to distinguish event data and bad data by using the slope feature of each set of data. Then, a bad data detection method based on spectral clustering is described. By analyzing the weighted relationships among all the data, this method can detect the bad data that has a small deviation.