Performance analysis for the robustness of MNMR state estimation in power system

The state estimation for power system which is based on the theory of uncertainty in measurement and takes the maximum normal measurement rate (MNMR) as its objective function has a good performance of robustness (bad data rejection). In this paper, the principle of good performance of bad data rejection is analyzed theoretically. Then, the robustness of the MNMR state estimation to different types of bad data is analyzed from different aspects, such as one bad data with different errors, multiple bad data of one single type and multiple types of bad data. Simulation results show that the MNMR state estimation has a different robustness to different types of bad data. In general, the MNMR state estimation has a strong ability to reject the bad data of power injection, however, it has a relatively poor ability to reject the bad data of bus voltage and line power flow.