Abstract-Transient stability analysis is performed to assess the power system's condition after a severe contingency and is carried out using simulations. To adequately assess the system's transient stability, the correct dynamic models for the machines (i.e., generators, condensers, and motors) along with their dynamic parameters must be defined. The IEEE test systems contain the data required for steady-state studies. However, neither the dynamic model of the machines nor their specific parameters have been established for transient studies. As a result, there is a demand for test bed systems suitable for transient analysis. This paper defines dynamic machine models along with their parameters for each IEEE test bed system, thus producing full dynamic models for all test systems. It is important to mention that the parameters of the proposed dynamic models are based on typical data. The test systems are subjected to large disturbances and a case study for each test system, which examines the frequency, angle, and voltage stability is presented. Further, the proposed dynamic IEEE test systems, implemented in PowerWorld, are available online.
The accurate knowledge of the transmission line parameters can be beneficial for several monitoring and control applications accommodated in the power system control center. Actually transmission line parameters are stored in the control center databases (assuming that they are time invariant); however, the databases might be obsolete and contain erroneous parameters. This paper proposes a methodology for identifying and estimating the erroneous transmission line parameters using measurements provided by Phasor Measurement Units (PMUs) and estimated states provided by a state estimator. The main advantage of the proposed methodology is that for the identification of the erroneous transmission lines and the estimation of the line parameters only one PMU is required for the monitoring of the transmission line (i.e., capture measurements related to the transmission line). The proposed methodology is tested in the IEEE 14-and 118-bus systems.
The state estimator constitutes the cornerstone of the supervisory control and data acquisition system since it provides the power system operating situation in consecutive time intervals. Furthermore, the output of the state estimator is used by other tools responsible for the monitoring and control of the power system. Therefore, there is a need for the power system state estimator to be as accurate and reliable as possible. The main source of uncertainty that may deteriorate the accuracy of a weighted least squares (WLS) state estimator, provided that the network parameters are perfectly known, is the uncertainty that is encompassed in the measurements. It is well known that the measurement chain is not ideal and this information is passed to the state estimator through the measurement weights. In this paper, the effect of the measurement weights, which are calculated by considering both the standard uncertainties associated with the measurement devices and the instrument transformers, on the WLS state estimator is examined.
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