This paper presents a response-based generating rejection scheme (GRS) based on an angular stability prediction logic to initiate the outage of accelerated generating units while saving the rest of generating units from the loss of synchronism. First trigonometric, polynomial, and hybrid models of rotor angle trajectory based on the reasonable assumptions are proofed. Then, by taking these models in the prediction step, through the maximum use of measured data based on defining the forecast horizon (FH) and data window with incremental length, the stability/instability of generating units is separately predicted. Next, the status of tripping signal based on a combinational logic of the output results of the angular stability prediction method is specified. In the developed logic, if at least two models of the three designated models yield the same response about the unit stability status, the trip signal is accordingly fired or blocked. The proposed method is examined on the one machine infinite bus and the WSCC standard test bed under different operation and fault scenarios. The obtained results demonstrate that beside simplicity, low computational burden, and very short processing time, the proposed combinatorial method outperforms the existing ones working with individual prediction models.
In this paper, rst, a rotor angle trajectory model based on polynomial functions is proposed. Afterwards, a response-based approach to the online prediction of the angular instability of a power system is presented. The proposed method utilizes bus phase angle data measured by a Phasor Measurement Unit (PMU) at a Point of Common Coupling (PCC) of the power plant transformer to the bulk power grid. In the prediction process, by computing the second-order derivative of post-fault data, the starting point of the calculation Data Window (DW) is determined. Next, a fth-degree polynomial curve is tted to the designated DW to predict the angular curve of a generating unit. Based on the sign of the rst-order derivative of the predicted curve, the angular stability of the generating unit is judged. This approach is testi ed on the western system coordinating council standard test bed under di erent operation and fault-type scenarios. By taking into account various fault conditions and their associated occurrence probability, a probabilistic index is also de ned to sum up the overall performance of the new method. Simulation results con rm that the proposed method outperforms the existing ones in terms of both accuracy and speed. Prediction results could be used in Generator Rejection Schemes (GRS) to prevent severe power plant outages.
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