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.