ISPEC 11th INTERNATIONAL CONFERENCE ON ENGINEERING & NATURAL SCIENCES, Muş, Turkey, 17 - 18 September 2021, pp.120-128
State estimation problem is of great importance for the operating conditions of a power system. The purpose of the state estimation is to know the voltage magnitude and angle value of all bus in the power system. Measurement data is needed to make a state estimation. These measurement data are obtained from Supervisory Control And Data Acquisition (SCADA) or Phasor Measurement Units (PMU) measurement devices. However, these measurement data contain some errors due to measurement errors, such as telemetry errors, communication noise etc. Furthermore, these bad data in the measurement data greatly affect the results of the state estimation. The Weighted Least Squares (WLS) method is widely used in the state estimation problem. In this study, Chi-squares test was used to determine whether there is bad data in a measurement data set. Firstly, state estimation with normal measurement data set was made in three different test systems. Afterwards, bad data was added by intentionally changing some of the data sets. The state estimation results in two different situations were compared and it was seen that the results were faulty. Whether there is bad data in the measurement data set was checked with the Chi-squares test. Measurement datasets containing bad data were successfully detected with the Chi-squares test. Finally, this study show that erroneous data in the measurement data, which is of great importance for the state estimation problem, are successfully detected.