A linear recursive bad data identification method with real-time application to power system state estimation

The recursive measurement error estimation identification (RMEEI) method for bad data (BD) analysis is described. By using a set of linear recursive formulae, state variables, residuals, and their variances are updated after the removal of a measurement from suspected data set to the remaining data set (or in the reverse direction). Neither a reestimation nor residual sensitivity matrix is needed in the identification process, which increases the computational speed greatly. Digital tests have been done to compare the RMEEI method with other conventional BD identification method in identification performance and computational speed. The real-time operation experience of the RMEEI method in energy management system (EMS) of the North East China power system control center is given