| Title |
Two-Step State Estimation Using PMU data for Fast Detection of Bad Data in Power Systems |
| Authors |
김병호(Byoung-Ho Kim) ; 김홍래(Hongrae Kim) |
| DOI |
https://doi.org/10.5370/KIEE.2020.69.7.993 |
| Keywords |
PMU; State Estimation; Bad Data Processing |
| Abstract |
As the dependence on electrical energy increases, the power system is becoming lager. Since the size of power system is gradually increasing, the calculation of various power system analysis applications used to check the current state of the power system is complicated and may consume a lot of calculation time. In addition, due to the aging of the power system, it is difficult to maintain the precision of the measuring instrument, and when a large number of bad data are included in the measurement set, a lot of time may be spent detecting and identifying them. The factor that determines the computation time of state estimation is related to the size of the system. When the measurement includes a number of bad data, most of the computation time in state estimation is consumed to process the bad data. If the power system can be divided into small scales to reduce the size of the system, the calculation time and the bad data detection of state estimation can be improved. When the state estimation is performed on the partitioned system, the estimated voltage magnitudes are same as the result of the original whole system. When the state estimation is performed on the partitioned small-scale systems, the voltage angles are calculated as angle differences with respect to the slack buses for each small-scale systems. If PMUs are installed for each small-scale systems, it is possible to recognize the difference in phase angle for each partitioned system. It is possible to perform a two-step state estimation, which consists of performing the state estimation of a partitioned system and correcting the phase angle of partitioned system using PMU measurement. In this paper, we propose a method to perform state estimation in two steps on a partitioned system using PMU measurement to shorten the calculation time of the state estimation and the detection time of the bad data for the large-scaled system. |