Dynamic estimation of power system stability in different Kalman filter implementations
Voltage collapse is still the biggest threat to the transmission system. There are many approaches that have been explored to predict the point of voltage collapse. However, it is still lacking of information that related to current system state. With the advancement of Phasor Measurement Units (PMU...
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| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/5406/ http://eprints.uthm.edu.my/5406/2/Dynamic_Estimation_of_Power_System.pdf |
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| Summary: | Voltage collapse is still the biggest threat to the
transmission system. There are many approaches that have
been explored to predict the point of voltage collapse.
However, it is still lacking of information that related to
current system state. With the advancement of Phasor
Measurement Units (PMUs) technology, it provides an
alternate pathway to improve the existing power system state
estimation. Hence, it was of interest to develop better
methods that could give a preliminary warning before the
voltage collapse. This paper concerns for the development of
real-time system monitoring methods to give a timely
warning in the power system. The algorithm to predict the
points of collapse is based on the assumption that voltage
instability is closely related to the maximum load ability of a
transmission network. Therefore, the Thevenin impedance is
equalled to the apparent load impedance at the points of
collapse. Numerous methods such as Discrete Kalman Filter
(Dm), Extended Kalman Filter (EKF) and Unscented
Kalman Filter (UKF) are being implemented into the realtime
voltage instability predictor to track the Thevenin
parameters. The test results are tested on Malaysia's power
system 132 kV - 2-bus and 10-bus systems. The results are
compared based on the early-warning index of voltage
collapse. The results of DKF method are set as the reference
for comparison purpose between EKF method and UKF
method. The test results shown that EKF method provided
better results by decreasing of 0.1169 p.u. for 2-bus system
and 0.0338 p.u. for 10-bus system. In the meanwhile, UKF
method provided increasing values of 0.4262 p.u. for 2-bus
system and 0.1522 p.u. for 10-bus system. The overall
purpose of this research is to develop methods that in
provide early warning for an emerging stability problem. In
order to achieving the research's objectives, derivation of the
index for early warning of the point of collapse is completed.
The performance of each method used throughout this
research is based on the analyzed results for the points of
voltage collapse. |
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